CN104268678A - Preventative device maintenance method based on dynamic reliability - Google Patents

Preventative device maintenance method based on dynamic reliability Download PDF

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CN104268678A
CN104268678A CN201410468975.7A CN201410468975A CN104268678A CN 104268678 A CN104268678 A CN 104268678A CN 201410468975 A CN201410468975 A CN 201410468975A CN 104268678 A CN104268678 A CN 104268678A
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equipment
maintenance
data
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time
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CN104268678B (en
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程聂
杨锋
朱彤
王炼
沈拥军
张鹏
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WUHAN JIAN'AN PETROCHEMICAL ENGINEERING Co Ltd
WUHAN BRANCH SINOPEC CORP
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WUHAN JIAN'AN PETROCHEMICAL ENGINEERING Co Ltd
WUHAN BRANCH SINOPEC CORP
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    • G06Q10/063—Operations research, analysis or management
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Abstract

The invention discloses a preventative device maintenance method based on dynamic reliability and belongs to the technical field of petrochemical equipment management. The preventative device maintenance method based on the dynamic reliability comprises the following steps of 1 establishing a device basic database including equipment accounts, historical maintenance and repair data, a fault strength analysis data, operation monitoring data and the like; 2 utilizing basic data to conduct operation time analysis, fault strength analysis and alarm state and operation trend analysis on devices; 3 utilizing results to establish a device reliability level and fault strength incidence matrix, formulate DRBPM data analysis logic, automatically screen preventative maintenance devices and generate preventative maintenance planning reports of the devices; 4 examining, verifying and executing the preventative maintenance planning reports of the devices. The preventative device maintenance method based on the dynamic reliability can be used for dynamic analysis and management of states of petrochemical equipment, facilitate formulation of scientific and effective device maintenance measures and provide guarantee for timely device fault elimination and production continuity reliability and can be widely applied to the technical field of petrochemical equipment management.

Description

A kind of Preventive Equipment Maintenance method based on dynamic reliability
Technical field
The invention belongs to petrochemical equipment administrative skill field, be specifically related to a kind of Preventive Equipment Maintenance method based on dynamic reliability.
Background technology
Equipment is the basis of enterprise's production run, and the quality of equipment control and maintenance directly determines productive capacity and the level of enterprise.Petrochemical equipment generally has the features such as maximization, complicated, production serialization, its operational reliability and maintainability most important.At present, what domestic many petroleum chemical enterprises taked production equipment is traditional maintenance method, i.e. correction maintenance and periodic maintenance method.Correction maintenance also claims fault or corrective maintenance, is the maintenance carried out after device fails or performance reduce.The method randomness of this " with bad with repairing " is comparatively large, lacks necessary plan, once run into catastrophic failure or industrial accident its maintenance is ageing will be deteriorated.Periodic maintenance is the Early manifestation of preventative maintenance thought, the mode of have timing to change, repairing and make regular check on and arrange the mode of recent turnaround plan according to check result, general maintenance interval is shorter, scope and the degree of depth larger, equipment is more reliable.This maintenance database in prevention mechanical fault, reduce in serious industrial accident and played significant role, but what bring is the shortcomings such as maintenance cost is high, maintenance load is large thereupon, and the maintenance of equipment cycle also needs the experience that depends on to determine usually, lack scientific basis, some equipment is caused not damage and overhauled, this excessive maintenance not only can cause manpower and materials to lose, and also can reduce system reliability.More advanced method for maintaining is condition maintenarnce at present, and it is the development along with Condition Monitoring Technology and detecting instrument, and the state residing for equipment decides the method for maintaining of maintenance timing.The advantage of condition maintenarnce is by strengthening and improving monitoring means, the duty of grasp equipment, Timeliness coverage problem also takes Corresponding Countermeasures, and some fault was effectively prevented before generation, and some catastrophic failure can be controlled when there is minor failure sign and get rid of.Condition maintenarnce can solve the problem of " this is repaiied and can not repair, and should not repair and but will repair " in periodic maintenance, and maintenance job is changed from passive to active, thus reduces failure rate, reduces maintenance range, reduces maintenance load, saves maintenance cost, improves plant factor simultaneously.But condition maintenarnce limits by the level of understanding, technical conditions, usually make the detection of device systems inaccurate, thus can affect accuracy and the validity of maintenance; Meanwhile, condition maintenarnce needs higher testing staff and instrument and equipment to drop into, and can not eradicate equipment failure.Maintenance (RCM, Reliability Centered Maintenance) centered by reliability is the main flow direction of current device maintenance correlative study.It take Inherent Equipment Reliability as the starting point, for fault observer and the character of distinct device, by specific logic decision analytical approach, determines equipment scheduled maintenance project, maintenance mode and best servicing time.RCM method is based upon on the basis of fault mode, fault effects and fault effects analysis, be a kind of maintenance mode that correction maintenance, periodic maintenance, condition maintenarnce etc. are combined, facts have proved that RCM method can effectively improve equipment reliability of operation and reduce maintenance cost.Although the architecture of RCM analytical approach basically forms, but the current theoretical analysis to RCM and applied research mainly concentrate on to be analyzed qualitatively, quantitative examination work is few, awaits further improving and development, especially in practicality, specific aim and accuracy etc.Carrying out the work greatest difficulty that runs into of RCM is lack effective reliability data and mantenance data, the reliability that tradition RCM method obtains is " static state ", and in reality these valid data often along with operation hours dynamic change, therefore be necessary very much to carry out Preventive Equipment Maintenance work based on " dynamic reliability ", to effectively utilizing Maintenance Resource, realize equipment long period reliability service.
Summary of the invention
The present invention is directed to petrochemical production equipment and propose a kind of Preventive Equipment Maintenance (DRBPM based on dynamic reliability, Dynamic Reliability Based Preventive Maintenance) method, utilize the network information technology and large data operation, set up different times equipment dynamic reliability, equipment failure strength grade associates with usability consequence, and be aided with equipment running status monitoring and trend anticipation data, by logic decision determination equipment Maintenance Policy, the dynamic management of the preventative work of the equipment that realizes, to integrating preventative maintenance to greatest extent, pre-emptive maintenace, the advantage of initiative maintenance, fault maintenance is down to minimum, thus passive maintenance can be avoided to greatest extent, specific aim and by force ageing, decision science, efficiently.
Specifically, a kind of Preventive Equipment Maintenance (DRBPM) method based on dynamic reliability provided by the invention, comprises the following steps:
Step one: apparatus for establishing basic database, the equipment Foundations data that Preventive Equipment Maintenance method uses comprise Unit account of plant data, device history checking maintenance data, equipment failure intensive analysis data and equipment operational monitoring data; Step 2: utilize basic data, carries out analysis working time, failure strength analysis, alarm condition and operation trend analysis to equipment respectively, utilizes device history checking maintenance data, computing equipment time between overhaul and mean time between failures; Utilize equipment failure grade and equipment use consequence basic data, carry out failure strength analysis, obtain the failure strength of every platform equipment; Utilize equipment operational monitoring data, obtain equipment alarm state, and carry out running trend of the equipment analysis; Step 3: utilize above analysis result, the incidence matrix between apparatus for establishing reliability level and failure strength, formulate DRBPM Data analysis logic, Automatic sieve selects the equipment needing to carry out preventative maintenance, generates Preventive Equipment Maintenance plan sheet; Step 4: carry out auditing to Preventive Equipment Maintenance plan sheet and perform, for the equipment needing to carry out preventative maintenance that computing machine Automatic sieve is selected, every month is audited it successively by equipment management personnel at different levels within the working day of regulation, the equipment carrying out preventative maintenance is agreed in motor-driven place keeper last instance, export as final monthly Preventive Equipment Maintenance plan sheet, be arranged in the corresponding equipment maintenance plan of next monthly execution.
In technique scheme, the equipment Foundations data described in described step one comprise: 1) Unit account of plant data, comprise device numbering, apparatus and process numbering, device category, unit type, date of manufacture, manufacturer, corresponding device; 2) device history checking maintenance data, comprise device numbering, apparatus and process numbering, overhaul of the equipments date and relevant maintenance content; 3) equipment failure intensive analysis data, comprise device numbering, apparatus and process numbering, failure strength grade, usability consequence, process constraints; 4) equipment operational monitoring data, comprise device numbering, apparatus and process numbering, equipment operation bearing state value, vibration values, temperature value and alarm condition.
In technique scheme, described step 2 comprises the following steps:
1) operation hours analysis: utilize device history checking maintenance data, computing equipment time between overhaul and mean time between failures, computing formula is respectively: T i=t cur-t lastwith MTBF=(t cur-D)/n, in formula, T irepresent time between overhaul, t currepresent current time, t lastthe indication equipment the last repair time, MTBF represents the mean time between failures, i.e. mean time between failures, for weighing device reliability level, repair time first time of D represents " same item " all devices, n represents " same item " the maintenance number of times of all devices in measurement period, " same item " equipment and same belonging to item equipment for subsequent use each other;
2) equipment failure intensive analysis: utilize equipment failure grade and equipment use consequence basic data, carry out failure strength analysis, obtain the failure strength of every platform equipment; According to equipment importance aborning and impact on activity in production and impact occur bonding apparatus fault, equipment failure strength grade L is divided into 6 grades, be expressed as 1 ~ 6 grade successively from high to low, wherein 1 grade of expression can cause full factory fluctuation, causes full factory to produce the amount of falling or multiple process units unplanned shutdown; 2 grades of expressions can cause single assembly unplanned shutdown, cause many covering devices fluctuation; 3 grades of expressions can cause the single process units amount of falling or local excision, and large-sized unit is suddenly stopped; 4 grades of expressions can cause single process units localised waving; 5 grades of expressions can cause single device to be stopped transport; 6 grades represent production without impact; According to petrochemical industry productive prospecting, equipment use consequence is divided into 3 kinds, i.e. S, E, N, wherein S represents serious safety consequence; E represents serious commercial consequence; N indicates that, without serious safety or economy consequence, the corresponding relation of equipment failure strength grade, equipment use consequence and equipment failure strength degree is as shown in the table:
Equipment failure strength grade Equipment use consequence Equipment failure strength degree
L＝1，2，3 S or E or N High
L＝4 S or E High
L＝4 N Low
L＝5 S or E High
L＝5 N Low
L＝6 S or E or N Low
3) equipment alarm state and operation trend analysis: utilize equipment operational monitoring data, obtain equipment alarm state, and carry out running trend of the equipment analysis, equipment alarm state reflection equipment current operating state, directly can extract corresponding field or utilize alarm threshold value to carry out real-time judge from current Monitoring Data, point " normally ", " one-level warning " and " secondary alarm " three state, running trend of the equipment reflects the equipment working state in section sometime, is the result to Historical Monitoring data analysis all in this time period, particularly, bearing state value is run to equipment, vibration values, the operation trend of temperature value is analyzed, the historical record of nearest one month of this equipment since maintenance last time has been read by monitoring point, wherein, reading by actual number of days less than one month, multiple monitoring point may be there is in the monitor value of every type, each monitoring point palpus independent analysis, analytical approach is described as: establish time series x (k), k=1, 2, ..., N comprises L value for certain monitoring point, V value or T value device history Monitoring Data, selected window size W, moving average process is carried out to sequence x (k), obtain moving average sequence on this basis to sequence carry out simple linear regression analysis, calculate A = Σ k = 1 N k , B = Σ k = 1 N k 2 , the best estimate that can obtain fitting a straight line parameter according to least square method is b ^ = B · C - A · D N · B - A 2 , Thus Recursive sequence y ( k ) = a ^ · k + b ^ , k = 1,2 , . . . , N , Calculate again thus as the increase trend of original series (i.e. this monitoring point survey data) x (k); After calculating the increase trend of all data of monitoring point, following judgement can be made to the operation trend of equipment: if arbitrary monitoring point L value increase trend be greater than setting threshold value or arbitrary monitoring point V value increase trend be greater than setting threshold value or arbitrary monitoring point T value increase trend be greater than set threshold value, then running trend of the equipment " poor "; Otherwise, running trend of the equipment " good ".
In technique scheme, described step 3 comprises the following steps: the incidence matrix between apparatus for establishing reliability level and failure strength P = [ P ( m , n ) ] 2 × 2 = P ( 0,0 ) P ( 0,1 ) P ( 1,0 ) P ( 1,1 ) , The wherein failure strength of m indicating equipment, m=0 represents that failure strength is low, and m=1 represents that failure strength is high, and the reliability level of n indicating equipment, works as T iduring >MTBF, n=0 (equipment current reliability level is lower), otherwise n=1 (equipment current reliability level is higher), P (m, n) then represent corresponding maintenance policy.In the present invention, P (1,0) is initiative preventability maintenance policy, represents that certain equipment failure intensity is high and lower in investigation time point reliability level, preventative maintenance strategy of should taking the initiative; P (0,0) and P (1,1) be pre-emptive maintenace strategy, represent that certain equipment failure intensity is low and lower in investigation time point reliability level, or this equipment failure intensity is high and higher in investigation time point reliability level, all should take pre-emptive maintenace strategy; P (0,1) is correction maintenance strategy, represents that certain equipment failure intensity is low and higher in investigation time point reliability level, can take correction maintenance strategy.Every platform equipment can find its correspondence position in this incidence matrix, according to different P (m, n) value, can make the method for maintaining that corresponding DRBPM Data analysis logic decision flow chart is determined to be suitable for.Particularly, in the present invention, DRBPM Data analysis logic is according to the time between overhaul T of every platform equipment i, mean time between failure, failure strength, alarm condition and operation trend comprehensively analyze further, the checking maintenance state of determining apparatus is the one in PM1, PM2, PM3, PM4, PM5, OP or PS, wherein: 1) PM1 represents the equipment of " in-service not repairing of exceeding the time limit, but normal operation "; 2) PM2 represents the equipment of " failure strength is high, be in one-level alarm condition, operation trend is poor, reach Inspection interval "; 3) PM3 represents the equipment of " failure strength high, be in secondary alarm state "; 4) PM4 represents the equipment of " be in secondary alarm state, reach Inspection interval "; 5) PM5 represents the equipment of " failure strength is high, operation trend is poor, reach Inspection interval "; 6) OP represents the equipment of " needing to pay close attention to ", and comprise two kinds of situations, one is equipment normal operation, has reached its Inspection interval, though two is that equipment does not reach its Inspection interval, but running status has degradating trend; 7) PS represents the equipment of " normal operation "; Wherein, " in-service not repairing of exceeding the time limit " refers to " time between overhaul be greater than setting threshold value ", i.e. T i>Th, is provided with different threshold values to the high equipment of failure strength and the low equipment of failure strength in the present invention, is expressed as ThH and ThL; " reach Inspection interval " and refer to " time between overhaul is greater than the mean time between failures ", be i.e. T i>MTBF; The equipment that all checking maintenance states are judged as PM1, PM2, PM3, PM4 or PM5 is the Preventive Equipment Maintenance method Data analysis logic automatic screening equipment needing to implement preventative maintenance out, can export as Preventive Equipment Maintenance plan sheet.
The Preventive Equipment Maintenance method of the present invention based on dynamic reliability, there is following beneficial effect: the present invention makes full use of status information, operational monitoring data and the history checking maintenance information that production equipment constantly changes, carry out equipment dynamic reliability analysis, form scientific and effective plant maintenance measure, change correction maintenance is preventative maintenance, become passive maintenance into Proactive maintenance, thus remover apparatus fault, guarantee continuous production are carried out and reduce maintenance cost in time, specific aim and by force ageing, decision science, efficient.
Accompanying drawing explanation
Fig. 1 is the main flow chart of the Preventive Equipment Maintenance method of the present invention based on dynamic reliability;
Fig. 2 is the mathematical logic analysis process figure in the Preventive Equipment Maintenance method step three of the present invention based on dynamic reliability;
Fig. 3 is the process flow diagram of the comprehensive analytical procedure of carrying out in the Preventive Equipment Maintenance method step three of the present invention based on dynamic reliability when mathematical logic is analyzed.
Embodiment
Below in conjunction with drawings and Examples, embodiments of the present invention are described in detail, but this embodiment should not be construed as limitation of the present invention.
See Fig. 1, a kind of Preventive Equipment Maintenance (DRBPM) method based on dynamic reliability described in the invention, comprises the following steps:
Step one: apparatus for establishing basic database, the equipment Foundations data that Preventive Equipment Maintenance method uses comprise: 1) Unit account of plant data, comprise device numbering, apparatus and process numbering, device category, unit type, date of manufacture, manufacturer, corresponding device; 2) device history checking maintenance data, comprise device numbering, apparatus and process numbering, overhaul of the equipments date and relevant maintenance content; 3) equipment failure intensive analysis data, comprise device numbering, apparatus and process numbering, failure strength grade, usability consequence, process constraints; 4) equipment operational monitoring data, comprise device numbering, apparatus and process numbering, equipment operation bearing state value L, vibration values V, temperature value T and alarm condition;
Step 2: utilize equipment Foundations data, respectively analysis working time, failure strength analysis, alarm condition and operation trend analysis are carried out to equipment, comprise the following steps:
1) operation hours analysis: utilize device history checking maintenance data, computing equipment time between overhaul and mean time between failures (MTBF, Mean Time Between Failures), computing formula is respectively: T i=t cur-t lastwith MTBF=(t cur-D)/n., in formula, T irepresent time between overhaul, t currepresent current time, t lastthe indication equipment the last repair time, MTBF represents the mean time between failures, i.e. mean time between failures, for weighing device reliability level, repair time first time of D represents " same item " all devices, n represents " same item " the maintenance number of times of all devices in measurement period, " same item " equipment and same belonging to item equipment for subsequent use each other, as: namely 1# catalytic unit P207/A, P207/B two pumps belongs to same item P207, and point A, B are for subsequent use each other;
2) equipment failure intensive analysis: utilize equipment failure grade and equipment use consequence basic data, carry out failure strength analysis, obtains the failure strength (high or low) of every platform equipment;
According to equipment importance aborning and impact on activity in production and impact occur bonding apparatus fault, equipment failure strength grade L is divided into 6 grades, be expressed as 1 ~ 6 grade successively from high to low, wherein 1 grade of expression can cause full factory fluctuation, causes full factory to produce the amount of falling or multiple process units unplanned shutdown; 2 grades of expressions can cause single assembly unplanned shutdown, cause many covering devices fluctuation; 3 grades of expressions can cause the single process units amount of falling or local excision, and large-sized unit is suddenly stopped; 4 grades of expressions can cause single process units localised waving; 5 grades of expressions can cause single device to be stopped transport; 6 grades represent production without impact; According to petrochemical industry productive prospecting, equipment use consequence is divided into 3 kinds, i.e. S, E, N, wherein S represents serious safety consequence, as fire after fault, and poisonous and harmful dielectric leakage; E represents serious commercial consequence, as more than 100,000 costs of repairs or import equipment; N indicates that, without serious safety or economy consequence, the corresponding relation of equipment failure strength grade, equipment use consequence and equipment failure strength degree is as shown in the table:
Equipment failure strength grade Equipment use consequence Equipment failure strength degree
L＝1，2，3 S or E or N High
L＝4 S or E High
L＝4 N Low
L＝5 S or E High
L＝5 N Low
L＝6 S or E or N Low
In addition, when manufacturing condition changes, will affect equipment failure grade or usability consequence, thus affect failure strength analysis result, relating generally to 3 kinds of situations needs to consider: 1) equipment departs from nominal situation point for a long time, and usability consequence changes to E; 2) apparatus and process condition changes, and there is severe safety or environmental risk, and failure strength grade rises 1 grade (notice that numeral is less, higher grade), and usability consequence changes to S; 3) apparatus and process condition changes, and continuous seepage is without stand-by equipment, and failure strength grade changes to 3 grades;
3) equipment alarm state and operation trend analysis: utilize equipment operational monitoring data, obtain equipment alarm state, and carry out running trend of the equipment analysis, equipment alarm state reflection equipment current operating state, directly can extract corresponding field or utilize alarm threshold value to carry out real-time judge from current Monitoring Data, point " normally ", " one-level warning " and " secondary alarm " three state; Running trend of the equipment reflects the equipment working state in section sometime, is the result to Historical Monitoring data analysis all in this time period;
Particularly, here refer to and bearing state value (L) is run to equipment, vibration values (V), the operation trend of temperature value (T) is analyzed, the historical record of nearest one month of this equipment since maintenance last time has been read by monitoring point, wherein, reading by actual number of days less than one month, multiple monitoring point may be there is in the monitor value of every type, each monitoring point palpus independent analysis, analytical approach is described as: establish time series x (k), k=1, 2, ..., N is device history Monitoring Data (the L value of certain monitoring point, V value or T value), selected sliding window size W (generally getting 3 ~ 5), moving average (MA is carried out to sequence x (k), Moving Average) process, obtain moving average sequence on this basis to sequence carry out simple linear regression analysis, calculate A = Σ k = 1 N k , B = Σ k = 1 N k 2 , the best estimate that can obtain fitting a straight line parameter according to least square method is a ^ = N · D - A · C N · B - A 2 , b ^ = B · C - A · D N · B - A 2 , Thus Recursive sequence y ( k ) = a ^ · k + b ^ , k = 1,2 , . . . , N , Calculate again thus as the increase trend of original series (i.e. this monitoring point survey data) x (k);
After calculating the increase trend of all data of monitoring point, following judgement can be made: if arbitrary monitoring point L value increase trend is greater than setting threshold value (namely showing as L value to worsen) or arbitrary monitoring point V value increase trend is greater than setting threshold value (namely showing as vibration to strengthen) or arbitrary monitoring point T value increase trend is greater than setting threshold value (namely showing as bearing temperature to raise), then running trend of the equipment " poor " to the operation trend of equipment; Otherwise, running trend of the equipment " good ";
Step 3: utilize above analysis result, incidence matrix between apparatus for establishing reliability level and failure strength, formulate DRBPM Data analysis logic, Automatic sieve selects the equipment needing to carry out preventative maintenance, generate Preventive Equipment Maintenance plan sheet, comprise the following steps:
Incidence matrix between apparatus for establishing reliability level and failure strength P = [ P ( m , n ) ] 2 × 2 = P ( 0,0 ) P ( 0,1 ) P ( 1,0 ) P ( 1,1 ) , The wherein failure strength of m indicating equipment, m=0 represents that failure strength is low, and m=1 represents that failure strength is high, and the reliability level of n indicating equipment, works as T iduring >MTBF, n=0 (equipment current reliability level is lower), otherwise n=1 (equipment current reliability level is higher), P (m, n) then represent corresponding maintenance policy.In the present invention, P (1,0) is initiative preventability maintenance policy, represents that certain equipment failure intensity is high and lower in investigation time point reliability level, preventative maintenance strategy of should taking the initiative; P (0,0) and P (1,1) be pre-emptive maintenace strategy, represent that certain equipment failure intensity is low and lower in investigation time point reliability level, or this equipment failure intensity is high and higher in investigation time point reliability level, all should take pre-emptive maintenace strategy; P (0,1) is correction maintenance strategy, represents that certain equipment failure intensity is low and higher in investigation time point reliability level, can take correction maintenance strategy.In actual implementation process, when taking the initiative preventative maintenance or correction maintenance strategy, existing equipment running status Monitoring Data also can be utilized suitably to be aided with pre-emptive maintenace strategy as a supplement.Every platform equipment can find its correspondence position in this incidence matrix, according to different P (m, n) value, can make the method for maintaining that corresponding DRBPM Data analysis logic decision flow chart is determined to be suitable for.Particularly, see Fig. 2 to Fig. 3, in the present invention, DRBPM Data analysis logic is according to the time between overhaul of every platform equipment, mean time between failures (MTBF), failure strength (high or low), alarm condition and operation trend (good or poor) comprehensive analysis further, the checking maintenance state of determining apparatus is the one in PM1, PM2, PM3, PM4, PM5, OP or PS, wherein:
1) PM1 represents the equipment of " in-service not repairing of exceeding the time limit, but normal operation ";
2) PM2 represents the equipment of " failure strength is high, be in one-level alarm condition, operation trend is poor, reach Inspection interval ";
3) PM3 represents the equipment of " failure strength high, be in secondary alarm state ";
4) PM4 represents the equipment of " be in secondary alarm state, reach Inspection interval ";
5) PM5 represents the equipment of " failure strength is high, operation trend is poor, reach Inspection interval ";
6) OP represents the equipment of " needing to pay close attention to ", and comprise two kinds of situations, one is equipment normal operation, has reached its Inspection interval, though two is that equipment does not reach its Inspection interval, but running status has degradating trend;
7) PS represents the equipment of " normal operation ";
Here, " in-service not repairing of exceeding the time limit " refers to " time between overhaul be greater than setting threshold value ", i.e. T i>Th, is provided with different threshold values to the high equipment of failure strength and the low equipment of failure strength in the present invention, is expressed as ThH and ThL; " reach Inspection interval " and refer to " time between overhaul is greater than the mean time between failures ", be i.e. T i>MTBF;
See Fig. 2, according to equipment failure strength degree, set different threshold value ThH and ThL, first setting threshold value whether is exceeded according to repair time interval, determining apparatus is " the non-in-service equipment that exceeds the time limit " and " exceed the time limit in-service equipment ", for " the non-in-service equipment that exceeds the time limit ", see Fig. 3, be PM2, PM3, PM4, PM5, OP or PS by comprehensive analytical procedure direct determining apparatus checking maintenance state; For " exceed the time limit in-service equipment ", when comprehensive analysis module determining apparatus checking maintenance state is PM2, PM3, PM4 or PM5, maintain this result of determination, and when comprehensive analysis module determining apparatus checking maintenance state is OP or PS, needing to revise result of determination is PM1;
The equipment that all checking maintenance states are judged as PM1, PM2, PM3, PM4 or PM5 is the Preventive Equipment Maintenance method Data analysis logic automatic screening equipment needing to implement preventative maintenance out, can export as Preventive Equipment Maintenance plan sheet;
Step 4: carry out auditing to Preventive Equipment Maintenance plan sheet and perform, for the equipment needing to carry out preventative maintenance that computing machine Automatic sieve is selected, every month is audited it successively by equipment management personnel at different levels (as appliance arrangement person, checking maintenance technician and motor-driven keeper) within the working day of regulation, the equipment carrying out preventative maintenance is agreed in motor-driven place keeper last instance, export as final monthly Preventive Equipment Maintenance plan sheet, be arranged in the corresponding equipment maintenance plan of next monthly execution.
Be below a specific embodiment of the present invention:
The Preventive Equipment Maintenance plan information management system that this embodiment is set up for full factory 2000 multiple stage pump equipment for Wuhan Branch Company SINOPEC,
The source of the equipment Foundations data used is respectively:
(1) Unit account of plant data are from Sinopec EM (equipment control) system;
(2) device history checking maintenance data are from Sinopec EM system;
(3) equipment failure intensive analysis data are provided by Wuhan Branch Company SINOPEC;
(4) equipment operational monitoring data are associated by Wuhan Branch Company SINOPEC monitoring of equipment platform, provide data access interface.
Generally, pump equipment bearing state value L has 2 measuring points, i.e. front end L value and rear end L value; Vibration values V has 5 measuring points, i.e. vertical vibration after horizontal vibration, pump after vertical vibration before horizontal vibration, pump, pump before axial vibration, pump; Temperature value T has 2 measuring points, i.e. temperature after temperature and pump before pump, in this embodiment, carry out analyzing the moving window W=3 judging to use to the operation trend of pump equipment, the threshold value of L, V, T value used is set as 20%, 20% and 30% respectively, in addition, ThH=30 month, ThL=42 month are respectively to the repair time interval threshold set by the high equipment of failure strength and the low equipment of failure strength.
The operation conditions of every platform pump equipment that Preventive Equipment Maintenance plan information management system meeting every day timing automatic analyzes also screens the equipment needing to carry out preventative maintenance, equipment management personnel (comprises appliance arrangement person, checking maintenance technician and motor-driven place managerial personnel) as long as logging device preventive maintenance schedule information management system, just can see the operation conditions of every platform pump, and the pump maintenance information that system generates automatically is judged, process, monthly regulation 1-20 day proposes report Preventive Equipment Maintenance plan by appliance arrangement person according to computer prompted signal auditing, 20-22 day is audited the maintenance schedule that appliance arrangement person carries report again by checking maintenance technician, 22-24 day carries out final review by motor-driven managerial personnel, the equipment carrying out preventative maintenance is agreed to by motor-driven keeper's last instance, export as final monthly Preventive Equipment Maintenance plan sheet, be arranged in next monthly execution.
Practice shows, since Preventive Equipment Maintenance plan information management system is run, the preventative working level of Wuhan Branch Company SINOPEC pump equipment improves constantly, and pump equipment catastrophic failure greatly reduces.
Obviously, those skilled in the art can carry out various change and modification to the present invention and not depart from the spirit and scope of the present invention.Like this, if these amendments of the present invention and modification belong within the scope of the claims in the present invention and equivalent technologies thereof, then the present invention is also intended to comprise these change and modification.
The content be not described in detail in this instructions belongs to the known prior art of professional and technical personnel in the field.

Claims (4)

1. the Preventive Equipment Maintenance method based on dynamic reliability, is characterized in that, comprise the following steps:
Step one: apparatus for establishing basic database, the equipment Foundations data that Preventive Equipment Maintenance method uses comprise Unit account of plant data, device history checking maintenance data, equipment failure intensive analysis data and equipment operational monitoring data;
Step 2: utilize basic data, carries out analysis working time, failure strength analysis, alarm condition and operation trend analysis to equipment respectively, utilizes device history checking maintenance data, computing equipment time between overhaul and mean time between failures; Utilize equipment failure grade and equipment use consequence basic data, carry out failure strength analysis, obtain the failure strength of every platform equipment; Utilize equipment operational monitoring data, obtain equipment alarm state, and carry out running trend of the equipment analysis;
Step 3: utilize above analysis result, the incidence matrix between apparatus for establishing reliability level and failure strength, formulate DRBPM Data analysis logic, Automatic sieve selects the equipment needing to carry out preventative maintenance, generates Preventive Equipment Maintenance plan sheet;
Step 4: carry out auditing to Preventive Equipment Maintenance plan sheet and perform, for the equipment needing to carry out preventative maintenance that computing machine Automatic sieve is selected, every month is audited it successively by equipment management personnel at different levels within the working day of regulation, the equipment carrying out preventative maintenance is agreed in motor-driven place keeper last instance, export as final monthly Preventive Equipment Maintenance plan sheet, be arranged in the corresponding equipment maintenance plan of next monthly execution.
2. a kind of Preventive Equipment Maintenance method based on dynamic reliability according to claim 1, it is characterized in that, the equipment Foundations data described in described step one comprise:
1) Unit account of plant data, comprise device numbering, apparatus and process numbering, device category, unit type, date of manufacture, manufacturer, corresponding device; 2) device history checking maintenance data, comprise device numbering, apparatus and process numbering, overhaul of the equipments date and relevant maintenance content; 3) equipment failure intensive analysis data, comprise device numbering, apparatus and process numbering, failure strength grade, usability consequence, process constraints; 4) equipment operational monitoring data, comprise device numbering, apparatus and process numbering, equipment operation bearing state value, vibration values, temperature value and alarm condition.
3. a kind of Preventive Equipment Maintenance method based on dynamic reliability according to claim 1, it is characterized in that, described step 2 comprises the following steps:
1) operation hours analysis: utilize device history checking maintenance data, computing equipment time between overhaul and mean time between failures, computing formula is respectively: T i=t cur-t lastwith MTBF=(t cur-D)/n., in formula, T irepresent time between overhaul, t currepresent current time, t lastthe indication equipment the last repair time, MTBF represents the mean time between failures, i.e. mean time between failures, for weighing device reliability level, repair time first time of D represents " same item " all devices, n represents " same item " the maintenance number of times of all devices in measurement period, " same item " equipment and same belonging to item equipment for subsequent use each other;
2) equipment failure intensive analysis: utilize equipment failure grade and equipment use consequence basic data, carry out failure strength analysis, obtain the failure strength of every platform equipment; According to equipment importance aborning and impact on activity in production and impact occur bonding apparatus fault, equipment failure strength grade L is divided into 6 grades, be expressed as 1 ~ 6 grade successively from high to low, wherein 1 grade of expression can cause full factory fluctuation, causes full factory to produce the amount of falling or multiple process units unplanned shutdown; 2 grades of expressions can cause single assembly unplanned shutdown, cause many covering devices fluctuation; 3 grades of expressions can cause the single process units amount of falling or local excision, and large-sized unit is suddenly stopped; 4 grades of expressions can cause single process units localised waving; 5 grades of expressions can cause single device to be stopped transport; 6 grades represent production without impact; According to petrochemical industry productive prospecting, equipment use consequence is divided into 3 kinds, i.e. S, E, N, wherein S represents serious safety consequence; E represents serious commercial consequence; N indicates that, without serious safety or economy consequence, the corresponding relation of equipment failure strength grade, equipment use consequence and equipment failure strength degree is as shown in the table:
Equipment failure strength grade Equipment use consequence Equipment failure strength degree L＝1，2，3 S or E or N High L＝4 S or E High L＝4 N Low L＝5 S or E High L＝5 N Low L＝6 S or E or N Low
3) equipment alarm state and operation trend analysis: utilize equipment operational monitoring data, obtain equipment alarm state, and carry out running trend of the equipment analysis, equipment alarm state reflection equipment current operating state, directly can extract corresponding field or utilize alarm threshold value to carry out real-time judge from current Monitoring Data, point " normally ", " one-level warning " and " secondary alarm " three state; Running trend of the equipment reflects the equipment working state in section sometime, is the result to Historical Monitoring data analysis all in this time period;
Particularly, bearing state value is run to equipment, vibration values, the operation trend of temperature value is analyzed, the historical record of nearest one month of this equipment since maintenance last time has been read by monitoring point, wherein, reading by actual number of days less than one month, multiple monitoring point may be there is in the monitor value of every type, each monitoring point palpus independent analysis, analytical approach is described as: establish time series x (k), k=1, 2, ..., N comprises L value for certain monitoring point, the device history Monitoring Data of V value or T value, selected window size W, moving average process is carried out to sequence x (k), obtain moving average sequence on this basis to sequence carry out simple linear regression analysis, calculate A = Σ k = 1 N k , B = Σ k = 1 N k 2 , the best estimate that can obtain fitting a straight line parameter according to least square method is a ^ = N · D - A · C N · B - A 2 , b ^ = B · C - A · D N · B - A 2 , Thus Recursive sequence y ( k ) = a ^ · k + b ^ , k = 1,2 , . . . , N , Calculate again thus as the increase trend of original series (i.e. this monitoring point survey data) x (k);
After calculating the increase trend of all data of monitoring point, following judgement can be made to the operation trend of equipment: if arbitrary monitoring point L value increase trend be greater than setting threshold value or arbitrary monitoring point V value increase trend be greater than setting threshold value or arbitrary monitoring point T value increase trend be greater than set threshold value, then running trend of the equipment " poor "; Otherwise, running trend of the equipment " good ".
4. a kind of Preventive Equipment Maintenance method based on dynamic reliability according to claim 1, it is characterized in that, described step 3 comprises the following steps:
Incidence matrix between apparatus for establishing reliability level and failure strength P = [ P ( m , n ) ] 2 × 2 = P ( 0,0 ) P ( 0,1 ) P ( 1,0 ) P ( 1,1 ) , The wherein failure strength of m indicating equipment, m=0 represents that failure strength is low, and m=1 represents that failure strength is high, and the reliability level of n indicating equipment, works as T iduring >MTBF, n=0 (equipment current reliability level is lower), otherwise n=1 (equipment current reliability level is higher), P (m, n) then represent corresponding maintenance policy.In the present invention, P (1,0) is initiative preventability maintenance policy, represents that certain equipment failure intensity is high and lower in investigation time point reliability level, preventative maintenance strategy of should taking the initiative; P (0,0) and P (1,1) be pre-emptive maintenace strategy, represent that certain equipment failure intensity is high and higher in investigation time point reliability level, or this equipment failure intensity is low and lower in investigation time point reliability level, should take pre-emptive maintenace strategy; P (0,1) is correction maintenance strategy, represents that certain equipment failure intensity is low and higher in investigation time point reliability level, can take correction maintenance strategy.Every platform equipment can find its correspondence position in this incidence matrix, according to different P (m, n) value, can make the method for maintaining that corresponding DRBPM Data analysis logic decision flow chart is determined to be suitable for.Particularly, in the present invention, DRBPM Data analysis logic is comprehensively analyzed further according to the time between overhaul of every platform equipment, mean time between failures, failure strength, alarm condition and operation trend, the checking maintenance state of determining apparatus is the one in PM1, PM2, PM3, PM4, PM5, OP or PS, wherein:
1) PM1 represents the equipment of " in-service not repairing of exceeding the time limit, but normal operation ";
2) PM2 represents the equipment of " failure strength is high, be in one-level alarm condition, operation trend is poor, reach Inspection interval ";
3) PM3 represents the equipment of " failure strength high, be in secondary alarm state ";
4) PM4 represents the equipment of " be in secondary alarm state, reach Inspection interval ";
5) PM5 represents the equipment of " failure strength is high, operation trend is poor, reach Inspection interval ";
6) OP represents the equipment of " needing to pay close attention to ", and comprise two kinds of situations, one is equipment normal operation, has reached its Inspection interval, though two is that equipment does not reach its Inspection interval, but running status has degradating trend;
7) PS represents the equipment of " normal operation ";
Wherein, " in-service not repairing of exceeding the time limit " refers to " time between overhaul be greater than setting threshold value ", i.e. T i>Th, is provided with different threshold values to the high equipment of failure strength and the low equipment of failure strength in the present invention, is expressed as ThH and ThL; " reach Inspection interval " and refer to " time between overhaul is greater than the mean time between failures ", be i.e. T i>MTBF.
The equipment that all checking maintenance states are judged as PM1, PM2, PM3, PM4 or PM5 is the Preventive Equipment Maintenance method Data analysis logic automatic screening equipment needing to implement preventative maintenance out, can export as Preventive Equipment Maintenance plan sheet.
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