CN109636060A - Wind turbines O&M working hour corrects prediction technique - Google Patents
Wind turbines O&M working hour corrects prediction technique Download PDFInfo
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- 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
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- 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—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
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Abstract
Provide a kind of Wind turbines O&M working hour amendment prediction technique; the described method includes: at least one O&M task of predetermined Wind turbines; the maintenance downtime section that first medium records is merged to determine at least one first merging maintenance downtime section, and the sequence of the sequence and corresponding record time data based on the maintenance shut-downs duration data of second medium record determines at least one second maintenance downtime section；At least one described first merging maintenance downtime section is compared at least one described second maintenance downtime section to obtain the amendment working hour of at least one O&M task；The prediction working hour that specific O&M task is completed by least one operation maintenance personnel is calculated based on the operation maintenance personnel of at least one O&M task described in the completion of the amendment working hour and first medium record.
Description
Technical field
This application involves wind-powered electricity generation fields, correct prediction technique more particularly, to a kind of Wind turbines O&M working hour.
Background technique
In the case where the background of renewable energy industry is supported energetically in the whole world, wind generating technology has obtained significant progress, degree
The electric continuous test of cost, it is gradually close to thermoelectricity.As domestic " the same valence of wind fire " policy is gradually implemented, the flat of Wind turbines is reduced
Standardization degree electricity cost (LCOE) becomes the important research direction that each complete machine quotient improves itself product competitiveness.Wind turbines are given birth to entirely
The cost in life period can simply be divided into unit cost, installation cost and O&M cost three parts, wherein preceding two-part phase
Pass technology has tended to be mature, and under the premise of can not break through industry and technical bottleneck, it is smaller to reduce space.With global total
Installed capacity is continuously increased, and the lean maintenance work of Wind turbines gradually becomes the emphasis for reducing the LCOE of Wind turbines,
Prospect can the phase.
Rationally assessment Wind turbines state, arranging efficient preventive maintenance work is the emphasis of lean O&M.However,
In the prior art, the O&M level of digital of Wind turbines is not generally up to standard, and task working hour, which is usually recorded by operation maintenance personnel, feeds back,
Accordingly, it is considered to complicated to live maintenance work environment, the record of work of manual feedback certainly exists distortion.
Summary of the invention
The one side of an exemplary embodiment of the present invention provides a kind of Wind turbines O&M working hour amendment prediction side
Method, which comprises at least one O&M task of predetermined Wind turbines, when the maintenance shut-downs that first medium is recorded
Between section merge with determine at least one first merge maintenance downtime section, and based on second medium record maintenance shut-downs
The sequence of duration data and the sequence of corresponding record time data determine at least one second maintenance downtime section；It will be described
At least one first merging maintenance downtime section is compared to obtain at least one described second maintenance downtime section
The amendment working hour of at least one O&M task；At least one described in completion based on the amendment working hour and first medium record
The operation maintenance personnel of a O&M task is completed the prediction working hour of specific O&M task to calculate by least one operation maintenance personnel.
The step of determining at least one second maintenance downtime section can include: when extracting maintenance shut-downs duration data jump
The corresponding time data that records is to obtain the sequence of maintenance shut-downs time data, and the sequence based on maintenance shut-downs time data is true
At least one fixed described second maintenance downtime section.
Maintenance shut-downs duration data can remain into the 2 significant digits of hour, and record time data can be according to scheduled duration
It is spaced and is recorded.
The step of determining at least one second maintenance downtime section based on the sequence of maintenance shut-downs time data can include:
Sequentially current maintenance shut-downs time data is compared with previous maintenance shut-downs time data, if when current maintenance shut-downs
The difference for carving data and previous maintenance shut-downs time data is much larger than specific duration, then from current maintenance shut-downs moment and previous shutdown
The sequence that maintenance shut-downs time data is split between the moment is safeguarded, to determine at least one described second maintenance downtime section；
Sequentially current record time data is compared with previous record time data, if current record time data with it is previous
Record time data difference be much larger than the scheduled duration interval, then by maintenance shut-downs corresponding to current record time data when
Long data subtract maintenance shut-downs duration data corresponding to previous record time data to obtain long data for the moment, and will be described when
Long data be added to the second maintenance downtime section corresponding to previous record time data or with current record time data
The second corresponding maintenance downtime section.
The step of obtaining the amendment working hour of at least one O&M task can include: if there is only an O&Ms to appoint
Business then subtracts each other the finish time of at least one second maintenance downtime section and start time to obtain described at least one
The amendment working hour of a O&M task；It, then will at least one described second maintenance downtime section if there is multiple O&M tasks
Finish time subtract each other with start time and subtract corresponding time of having a rest section again to obtain at least one described O&M task
Amendment working hour.
The step of calculating completes the prediction working hour of specific O&M task by least one operation maintenance personnel can include: pass through solution
Equation is completed the contribution rate of the specific O&M task to calculate by single operation maintenance personnel, and is based on being completed by single operation maintenance personnel
The contribution rate of the specific O&M task is completed the prediction work of the specific O&M task to calculate by least one operation maintenance personnel
When, wherein contribution rate indicates task Percent Complete per hour.
It is that the equation can be completed the contribution rate of the specific O&M task by multiple single operation maintenance personnels and be equal to described
Multiple single operation maintenance personnels complete the composition reciprocal in the corresponding amendment working hour of the specific O&M task.
The step of calculating completes the prediction working hour of the specific O&M task by least one operation maintenance personnel can include: pass through
It counts contribution rate summation that each operation maintenance personnel at least one operation maintenance personnel completes the specific O&M task is inverted
Calculate the prediction working hour that the specific O&M task is completed by least one described operation maintenance personnel.
The one side of an exemplary embodiment of the present invention provides a kind of computer readable storage medium, feature
It is, the computer-readable recording medium storage has makes processor execute above-mentioned Wind turbines when being executed by a processor
The program instruction of O&M working hour amendment prediction technique.
The one side of an exemplary embodiment of the present invention provides a kind of computing device characterized by comprising
Processor；Memory is stored with and processor is made to execute above-mentioned Wind turbines O&M working hour amendment when being executed by a processor
The program instruction of prediction technique.
It is artificial when making a report on can to correct objective reliably amendment working hour by working hour for an exemplary embodiment of the present invention
Error can be provided based on amendment working hour and comprehensively consider personnel using the working hour prediction technique with task category to calculate reliable work
When refer to, so as to reasonable arrangement O&M maintenance plan reduce wind field lean O&M cost.
Detailed description of the invention
By below with reference to be exemplarily illustrated an example attached drawing carry out description, above and other purpose of the invention and
Feature will become apparent, in which:
Fig. 1 is the process for showing Wind turbines O&M working hour amendment prediction technique according to an exemplary embodiment of the present invention
Figure；
Fig. 2 is to show the shutdown dimension according to an exemplary embodiment of the present invention there is only an O&M task
Protect the diagram of period；
Fig. 3 is to show the maintenance shut-downs according to an exemplary embodiment of the present invention there are multiple O&M tasks
The diagram of period；
Fig. 4 is to show the flow chart according to an exemplary embodiment of the present invention for calculating contribution rate.
Specific embodiment
Now, detailed description of the present invention exemplary embodiment, example indicate in the accompanying drawings, wherein identical label
Always show identical component.
Fig. 1 is the process for showing Wind turbines O&M working hour amendment prediction technique according to an exemplary embodiment of the present invention
Figure.
Referring to Fig.1, at least one O&M task of predetermined Wind turbines is recorded first medium in step S110
Maintenance downtime section merge with determine at least one first merge maintenance downtime section, and based on second medium remember
The sequence of the maintenance shut-downs duration data of record and the sequence of corresponding record time data determine at least one second maintenance shut-downs
Period.Here, merge maintenance downtime section for first, it can be directly by the maintenance downtime of at least one O&M task
Section takes union to merge processing.In addition, only as an example, not a limit, first medium can be work order, second medium can
To be by the SCADA data of the O&M task of Wind turbines record.When the SCADA data of Wind turbines record includes maintenance shut-downs
Between when maintenance personnel carry out on-site maintenance when, need Wind turbines state being tuned into maintenance shut-downs state, at this time in SCADA system
Maintenance downtime start to increase.Here, only as an example, not a limit, maintenance shut-downs duration data can remain into hour
2 significant digits, record time data can be recorded according to scheduled duration interval (such as, 8 seconds).More specifically, determining extremely
The step of few second maintenance downtime section may include the corresponding record moment when extracting maintenance shut-downs duration data jump
Data are to obtain the sequence of maintenance shut-downs time data (for example, recyclable compare maintenance shut-downs duration data, if current shut down
It safeguards that time data is greater than previous maintenance shut-downs time data, then current maintenance shut-downs time data is charged into the maintenance shut-downs moment
The sequence of data), and at least one second maintenance downtime section can be determined based on the sequence of maintenance shut-downs time data.This
Outside, only as an example, not a limit, the sequence based on maintenance shut-downs time data determines at least one second maintenance downtime
The step of section can include: be sequentially compared current maintenance shut-downs time data with previous maintenance shut-downs time data, such as
The difference of the current maintenance shut-downs time data of fruit and previous maintenance shut-downs time data is much larger than specific duration (such as, maintenance shut-downs
Duration data remain into corresponding 0.01 hour of the 2 significant digits of hour), then stop from the current maintenance shut-downs moment with previous
The sequence of maintenance shut-downs time data is split between the machine maintenance moment to be respectively formed the both ends of two maintenance downtime sections；It is suitable
Sequence current record time data is compared with previous record time data, if current record time data and previous note
The difference for recording time data is much larger than the scheduled duration interval (such as, 8 seconds), then will stop corresponding to current record time data
Machine maintenance duration data subtract maintenance shut-downs duration data corresponding to previous record time data to obtain long data for the moment, and
The duration data are added to and the second maintenance downtime section or and current record corresponding to previous record time data
Second maintenance downtime section corresponding to time data.
It, will at least one described first merging maintenance downtime section and at least one described second shutdown in step S120
Maintenance time section is compared to obtain the amendment working hour of at least one O&M task.Here, it is only used as example rather than limits
System, can be by least one described first merging maintenance downtime section and at least one described second maintenance downtime Duan Tong
Intraday data are compared.More specifically, if there is only an O&M task, can by it is described at least one second stop
The finish time and start time of machine maintenance time section subtract each other to obtain the amendment working hour of at least one O&M task；If
There are multiple O&M tasks, then can subtract each other the finish time of at least one second maintenance downtime section with start time
And subtract corresponding time of having a rest section again to obtain the amendment working hour of at least one O&M task.In addition, being deposited in determination
Before an O&M task or multiple O&M tasks, it may be determined that maintenance dates whether there is deviation, if there is deviation, then
Work order time record can be corrected by wind field project department.
Fig. 2 is the diagram for showing the maintenance downtime section there is only an O&M task.
As shown in (a) and (b) of Fig. 2, it can be seen that first merges maintenance downtime section and the second maintenance downtime
Certain otherness may be present in section.Although Wind turbines are spaced longer period of time in test run state in (a), its
Maintenance work does not complete simultaneously, until unit restores to operate normally 07 points when afternoon 4, the first merging maintenance downtime section is
1.67 hours, be 1.2 hours according to the second maintenance downtime section revised working hour.(b) in when the first merging maintenance shut-downs
Between section it is obviously less than normal, the two differ 3.2 hours.
Fig. 3 is the diagram for showing the maintenance downtime section there are multiple O&M tasks.
As shown in (a) of Fig. 3, Wind turbines perform two O&M tasks altogether, although have one section among Wind turbines
Between in test run state, but the first maintenance downtime for merging maintenance downtime segment record shows personnel in the work phase
Between there is no resting, actual conditions need to feed back to wind field project department and verify to subtract corresponding time of having a rest section, two fortune
Working hour needed for dimension task successively executes is between 5.19 hours to 5.35 hours.It is exactly the opposite with (a) as shown in (b) of Fig. 3,
Second maintenance downtime section is substantially continuous, and only in work finishing phase there are the test of 1 point half of unit starting, two O&Ms are appointed
Working hour needed for being engaged in is 2.25 hours.
In step S130, based at least one O&M task described in the completion for correcting working hour and first medium record
Operation maintenance personnel is completed the prediction working hour of specific O&M task to calculate by least one operation maintenance personnel.More specifically, can be by asking
It solves equation to calculate the contribution rate for completing the specific O&M task by single operation maintenance personnel, and based on complete by single operation maintenance personnel
The prediction that the specific O&M task is completed by least one operation maintenance personnel is calculated at the contribution rate of the specific O&M task
Working hour, wherein contribution rate indicates that task Percent Complete per hour, the equation complete the spy by multiple single operation maintenance personnels
The sum for determining the contribution rate of O&M task completes repairing accordingly for the specific O&M task equal to the multiple single operation maintenance personnel
The composition reciprocal in positive working hour.
Here, it can refer to Fig. 4 to describe the calculating of contribution rate.Fig. 4 is to show meter according to an exemplary embodiment of the present invention
Calculate the flow chart of contribution rate.Operation maintenance personnel and O&M task work order all the same are merged in step S410 referring to Fig. 4,
Taking average working hour is the working hour of O&M task.In step S420, for all work orders after merging, take O&M task i (i ∈ [1,
M], m is positive integer) work order of=1 (that is, O&M task 1), K is calculated by solving equationI=1, j ∈ [1, n], wherein j is to complete
The operation maintenance personnel of O&M task, n are positive integer.In step S430, determine whether i is m.If it is, process terminates；If no
It is then to take i=i+1 and return step S420.It should be noted that in the step s 420, in fact it could happen that cannot due to data deficiencies
Enough find out KI=1, j ∈ [1, n]The case where, it at this moment can equally proceed to step S430 and determine whether i is m.
Here, only as an example, not a limit, it is assumed that O&M task p is by tri- groups of different O&M people of A and B, B and C, A and C
When member completes, working hour spends h respectively1、h2、h3, then contribution rate can be calculated according to the multi head linear equation of following equation 1.
[equation 1]
Wherein, KP, AIndicate the contribution rate that O&M task p is completed by single operation maintenance personnel A, KP, BIt indicates by single O&M people
Member B completes the contribution rate of O&M task p, KP, CIndicate the contribution rate that O&M task p is completed by single operation maintenance personnel C.
In addition, more specifically, calculating the prediction working hour for completing the specific O&M task by least one operation maintenance personnel
Step can be summed by the way that each operation maintenance personnel at least one operation maintenance personnel to be completed to the contribution rate of the specific O&M task
It is inverted to calculate the prediction working hour that the specific O&M task is completed by least one described operation maintenance personnel.
That is, in the case where the contribution rate that known single O&M executes, single O&M task out counter can be inquired into
Working hour.Here, only as an example, not a limit, it is assumed that known KP, A、KP, B、KP, C, then can carry out calculating task p according to following equation 2
Working hour H needed for being completed jointly by A, B, C.
[equation 2]
It is artificial when making a report on can to correct objective reliably amendment working hour by working hour for an exemplary embodiment of the present invention
Error can be provided based on amendment working hour and comprehensively consider personnel using the working hour prediction technique with task category to calculate reliable work
When refer to, so as to reasonable arrangement O&M maintenance plan reduce wind field lean O&M cost.
According to example embodiment of the present invention, each step of the method for Fig. 1, Fig. 4 description can be written as program or soft
Part.It can be compiled based on the corresponding description in block diagram shown in the accompanying drawings and flow chart and specification using any programming language
Program writing or software.In one example, program or software may include directly being executed by one or more processors or computer
Machine code, such as, by compiler generate machine code.In another example, program or software include by one or
The more advanced code that multiple processors or computer use interpreter to execute.Program or software can be recorded, stores or be fixed on
In one or more non-transitory computer-readable storage medias.In one example, program or software or one or more non-
Temporary computer readable storage medium can be distributed in computer system.
The example embodiment conceived according to the present invention, Fig. 1, Fig. 4 description method each step can be implemented in including
On the computing device of processor and memory.Memory, which is stored with, realizes each unit as described above for control processor
The program instruction of operation.
Although specific example embodiments of the invention are described in detail above with reference to attached drawing, this hair is not being departed from
In the case where the spirit and scope of bright design, it can modify in a variety of manners to the present invention.If the technology of description is not with
Be sequentially executed, and/or if the component in the system of description, framework or device combines in different ways, and/or
It is replaced or is supplemented by other assemblies or their equivalent, then suitable result can be achieved.Therefore, the scope of the present disclosure is not logical
Cross specific embodiment to be limited, but be limited by the claims and their equivalents, and claim and they
All changes in the range of equivalent are to be interpreted as being included in the present disclosure.
Although the present invention has shown and described referring to certain exemplary embodiments, those skilled in the art will
Understand, shape can be made in the case where not departing from the spirit and scope of the present invention that range is defined by the claims and their equivalents
Various changes in formula and details.
Claims (10)
1. a kind of Wind turbines O&M working hour corrects prediction technique, which comprises
For at least one O&M task of predetermined Wind turbines, the maintenance downtime section that first medium records is merged
To determine at least one first merging maintenance downtime section, and the sequence of the maintenance shut-downs duration data based on second medium record
The sequence of column and corresponding record time data determines at least one second maintenance downtime section；
It will at least one described first merging maintenance downtime section and the progress of at least one described second maintenance downtime section
Compare to obtain the amendment working hour of at least one O&M task；
It is calculated based on the operation maintenance personnel of at least one O&M task described in the completion of the amendment working hour and first medium record
The prediction working hour of specific O&M task is completed by least one operation maintenance personnel.
2. Wind turbines O&M working hour as described in claim 1 corrects prediction technique, wherein determine at least one second shutdown
The step of maintenance time section includes:
Corresponding record time data to be when extracting maintenance shut-downs duration data jump to obtain the sequence of maintenance shut-downs time data,
And at least one described second maintenance downtime section is determined based on the sequence of maintenance shut-downs time data.
3. Wind turbines O&M working hour as claimed in claim 2 corrects prediction technique, wherein maintenance shut-downs duration data retain
To the 2 significant digits of hour, records time data and be recorded according to scheduled duration interval.
4. Wind turbines O&M working hour as claimed in claim 3 corrects prediction technique, wherein be based on maintenance shut-downs time data
Sequence the step of determining at least one second maintenance downtime section include:
Sequentially current maintenance shut-downs time data is compared with previous maintenance shut-downs time data, if current shut down dimension
The difference of time data and previous maintenance shut-downs time data is protected much larger than specific duration, then from the current maintenance shut-downs moment with it is previous
The sequence of maintenance shut-downs time data is split between the maintenance shut-downs moment, to determine at least one described second maintenance downtime
Section；
Sequentially current record time data is compared with previous record time data, if current record time data with
The difference of previous record time data is much larger than the scheduled duration interval, then ties up shutdown corresponding to current record time data
Shield duration data subtract maintenance shut-downs duration data corresponding to previous record time data to obtain a period of time long data, and by institute
State duration data be added to the second maintenance downtime section corresponding to previous record time data or with the current record moment
Second maintenance downtime section corresponding to data.
5. Wind turbines O&M working hour as described in claim 1 corrects prediction technique, wherein obtain at least one described O&M
The step of amendment working hour of task includes:
If there is only an O&M task, by the finish time of at least one second maintenance downtime section and beginning
Moment subtracts each other to obtain the amendment working hour of at least one O&M task；
If there is multiple O&M tasks, then by the finish time of at least one second maintenance downtime section and beginning when
Carve the amendment working hour for subtracting each other and subtracting again corresponding time of having a rest section to obtain at least one O&M task.
6. Wind turbines O&M working hour as described in claim 1 corrects prediction technique, wherein calculate by least one O&M people
Member completes the step of prediction working hour of specific O&M task and includes:
The contribution rate that the specific O&M task is completed by single operation maintenance personnel is calculated by solving equation, and based on by single
Operation maintenance personnel completes the contribution rate of the specific O&M task to calculate and complete the specific O&M by least one operation maintenance personnel
The prediction working hour of task,
Wherein, contribution rate indicates task Percent Complete per hour.
7. Wind turbines O&M working hour as claimed in claim 6 corrects prediction technique, wherein the equation is by multiple single fortune
It is that dimension personnel complete the contribution rate of the specific O&M task and be equal to the multiple single operation maintenance personnel and complete the specific fortune
The composition reciprocal in the corresponding amendment working hour of dimension task.
8. Wind turbines O&M working hour as claimed in claim 6 corrects prediction technique, wherein calculate by least one O&M people
Member completes the step of prediction working hour of the specific O&M task and includes:
Contribution rate by the way that each operation maintenance personnel at least one operation maintenance personnel to be completed to the specific O&M task, which is summed, to be taken
Inverse is completed the prediction working hour of the specific O&M task to calculate by least one described operation maintenance personnel.
9. a kind of computer readable storage medium, which is characterized in that the computer-readable recording medium storage has when processed
Device makes Wind turbines O&M working hour amendment prediction side described in any one of processor perform claim requirement 1 to 8 when executing
The program instruction of method.
10. a kind of computing device characterized by comprising
Processor；
Memory is stored with and makes wind described in any one of processor perform claim requirement 1 to 8 when being executed by a processor
The program instruction of motor group O&M working hour amendment prediction technique.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111260085A (en) * | 2020-01-09 | 2020-06-09 | 杭州中恒电气股份有限公司 | Device replacement man-hour evaluation method, device, equipment and medium |
| CN113409006A (en) * | 2021-05-27 | 2021-09-17 | 中核检修有限公司 | Method and device for calculating working hours in nuclear power overhaul and terminal |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060085218A1 (en) * | 2004-10-19 | 2006-04-20 | Freightliner Llc | Vehicle downtime reporting tool |
| US20140281712A1 (en) * | 2013-03-15 | 2014-09-18 | General Electric Company | System and method for estimating maintenance task durations |
| CN104268071A (en) * | 2014-10-23 | 2015-01-07 | 浙江力太科技有限公司 | Method for ensuring accuracy of stop timing of OEE (Overall Equipment Effectiveness) |
| US20150234675A1 (en) * | 2014-02-17 | 2015-08-20 | Cisco Technology, Inc. | System and method for process run-time prediction |
| CN106355307A (en) * | 2016-08-19 | 2017-01-25 | 许继集团有限公司 | Calculation method for wind turbine generator set availability of SCADA system |
| CN108830391A (en) * | 2018-06-20 | 2018-11-16 | 北京金风慧能技术有限公司 | Wind power generating set operation management system, method and computer equipment |
-
2018
- 2018-12-25 CN CN201811587670.2A patent/CN109636060A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060085218A1 (en) * | 2004-10-19 | 2006-04-20 | Freightliner Llc | Vehicle downtime reporting tool |
| US20140281712A1 (en) * | 2013-03-15 | 2014-09-18 | General Electric Company | System and method for estimating maintenance task durations |
| US20150234675A1 (en) * | 2014-02-17 | 2015-08-20 | Cisco Technology, Inc. | System and method for process run-time prediction |
| CN104268071A (en) * | 2014-10-23 | 2015-01-07 | 浙江力太科技有限公司 | Method for ensuring accuracy of stop timing of OEE (Overall Equipment Effectiveness) |
| CN106355307A (en) * | 2016-08-19 | 2017-01-25 | 许继集团有限公司 | Calculation method for wind turbine generator set availability of SCADA system |
| CN108830391A (en) * | 2018-06-20 | 2018-11-16 | 北京金风慧能技术有限公司 | Wind power generating set operation management system, method and computer equipment |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111260085A (en) * | 2020-01-09 | 2020-06-09 | 杭州中恒电气股份有限公司 | Device replacement man-hour evaluation method, device, equipment and medium |
| CN111260085B (en) * | 2020-01-09 | 2023-12-12 | 杭州中恒电气股份有限公司 | Device replacement man-hour assessment method, device, equipment and medium |
| CN113409006A (en) * | 2021-05-27 | 2021-09-17 | 中核检修有限公司 | Method and device for calculating working hours in nuclear power overhaul and terminal |
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