Method for online calculating number of repeated overhaul times of same fault of fan based on defect list

A technology of maintenance times and defect lists, applied in calculation, data processing applications, instruments, etc., can solve the problems of heavy analysis workload, inability to grasp the overall picture of wind farm production, and large time span, so as to achieve clear logic and improve enterprise operation. Dimensional analysis and decision-making level, and the effect of efficient operation and maintenance

Pending Publication Date: 2021-11-05
XIAN THERMAL POWER RES INST CO LTD +1
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AI-Extracted Technical Summary

Problems solved by technology

The current method is for wind farm operators to manually judge by reviewing the historical data of wind farm fan operation and maintenance. However, due to the large number of wind turbines, the large time span, and the heavy workload of analysis, it is ...
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Abstract

The invention discloses a method for online calculating the number of repeated overhaul times of the same fault of a fan based on defect lists, and the method comprises the following steps: 1) collecting the defect lists created on the same day of a statistical day T0 from a wind field production management system, and forming a set A0; 2) rejecting defect lists of which the states are temporary storage, canceling and discarding states from the set A0 to form a set A; 3) from the n defects of the set A, taking a defect fan ID + equipment KKS + defect phenomenon as a main key; 4) querying defect sheets with the same main key in a statistical time range from a wind field production management system by using the query main key Ki of each defect, and forming a defect sheet set Bi; 5) rejecting the defect sheets with the states of temporary storage, canceling and discarding from the defect sheet set Bi to form a set Ci; 6) enabling the number mi of the defects in the set Ci to be the number of times of repeated overhaul of the fan and the fault corresponding to the query main key Ki; and 7) returning to the step (4), continuing to calculate the repeated overhaul times of other fans and faults by taking Ki + 1 as a query main key until i + 1 is equal to n, and obtaining the number of times of repeated overhaul of the same fault in the statistical time range of the fan subjected to daily fault overhaul. The scientific and rapid index obtaining method is provided for a production management department.

Application Domain

Technology Topic

Time rangeOnline computation +8

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  • Method for online calculating number of repeated overhaul times of same fault of fan based on defect list
  • Method for online calculating number of repeated overhaul times of same fault of fan based on defect list

Examples

  • Experimental program(1)

Example Embodiment

[0018] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.
[0019] The method of the present invention to calculate the repeated maintenance times of the same fault of the wind turbine based on the defect single line has been tested on the wind power intelligent operation and maintenance project, and the automatic calculation on the intelligent operation and maintenance platform has been realized. important means of performance appraisal. Taking the headquarters of a wind power company as an example, the implementation of the method is introduced as follows:
[0020] 1) Collect and organize the field information of the three subordinate wind farm defect orders in the wind farm production management system, and extract the fields such as the state of the defect order, the ID of the defective fan, the equipment KKS, the phenomenon of the defect, and the time when the defect was created.
[0021] 2) The statistics program collects the defect order information of the previous day (statistical day) online at 1 o'clock in the morning every day to form the original defect order form.
[0022] 3) From the original defect list, select the defect list that was created on the day of statistics and whose status is not temporarily stored, canceled, or invalidated, to form a valid defect list.
[0023] 4) From the effective defect list, use the three fields of defective fan ID+equipment KKS+defect phenomenon as the query primary key to sort out the query primary key table;
[0024] 5) Use each query primary key in the query primary key table to query the defect orders with the same primary key within the statistical time range from the wind farm production management system, and the statistical time range is set to 1 year according to the requirements of the production management department;
[0025] 6) From the query result in the previous step, remove the defect list whose status is temporary storage, cancellation, invalidation, etc., then the number of the defect list is the number of repeated inspections of the fan and fault corresponding to the primary key of this round of query;
[0026] 7) Return to step 5), the next query primary key continues to calculate the number of repeated maintenance of other fans and faults, until the query of all query primary keys is completed;
[0027] 8) At this point, the number of repeated inspections of the same fault within the statistical time range of the fan that has a fault repair on the statistical day has been obtained online.
[0028] figure 1 For the number of repeated inspections (daily) of the same fault of the wind turbine, the index data required for the daily report of the previous day (statistical day) is automatically counted and calculated every morning, and displayed in the production daily report of the production management department. Users can flexibly query the subordinate wind farms on any date The number of repeated inspections of the fan for the same fault.
[0029] figure 2 For the comparison of repeated maintenance times for the same fault of the wind turbine (daily), to achieve benchmarking between wind farms.
[0030] figure 1 and figure 2 Among them, the user can choose the date arbitrarily, and query the number of repeated inspections of the same fault of the wind turbines of the subordinate wind farms, and together with the repeated inspection times index of the same wind turbine, it provides a basis for the user to grasp the overview of the repeated inspections of the wind turbines, and for the production management department to carry out operation and maintenance Level evaluation and benchmarking provide an objective and effective means.
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