KR102193838B1 - Q&m platform apparatus for supporting a maintenance of wind turbine based on scheduler - Google Patents

Abstract

The present invention relates to a Q&M platform apparatus for supporting maintenance of a wind turbine based on a scheduler. A Q&M platform apparatus for supporting maintenance of a wind turbine based on a scheduler, according to a preferred embodiment of the present invention, comprises a database, and a performance evaluation portion. The performance evaluation portion generates, by using information in the database, a wind turbine efficiency approximate curve function based on efficiency information of a wind turbine from a point of installation of the wind turbine to a point of time at which efficiency becomes less than or equal to an efficiency first threshold, when the efficiency of the wind turbine is less than or equal to the preset efficiency first threshold, calculates a performance index for each part based on sensed data collected from a point of time when the wind turbine is installed to a point of time at which efficiency becomes less than or equal to the efficiency first threshold, generates a part performance index approximate curve function for each part for the performance index, from the point of time at which the efficiency of the wind turbine becomes equal to or less than the efficiency first threshold value to the point of time at which the efficiency of the wind turbine becomes equal to or less than an efficiency second threshold value, evaluates the similarity between the wind turbine efficiency approximate curve function and the part performance index approximate curve function for each part, and specifies, as a replacement target part, a part having a part performance index approximate curve function having a similarity greater than or equal to a reference similarity, as a result of the similarity evaluation.

Description

Q&M platform device supporting maintenance of scheduler-based wind power generator {Q&M PLATFORM APPARATUS FOR SUPPORTING A MAINTENANCE OF WIND TURBINE BASED ON SCHEDULER}

The present invention relates to a scheduler-based wind power generation maintenance support Q&M platform device.

A wind power generator is a device that converts wind energy into electrical energy, and generates electricity by rotating the blades of the wind power generator using the rotational force of the blades. Wind power generation corresponds to clean energy that does not cause environmental pollution.

The main components of wind generators are blades, towers, forgings, gearboxes, bearings, generators and inverters.

Wind power generators are greatly affected by weather factors including real-time changing winds, which are external factors due to the characteristics of wind power generation.

In the case of wind power generation, the amount of impact applied to the facility becomes larger than that of other power generation facilities, and thus, there is a difficult problem in the critical life of each part or component.

1. Korean Patent Registration No. 10-1757117 (wind power generator maintenance device and method, registered on July 05, 2017)

An object of the present invention is to propose a Q&M platform device capable of supporting a scheduler-based wind power generation maintenance based on information collected from wind power generation.

According to a preferred embodiment of the present invention, a scheduler-based wind power generation maintenance support Q&M platform device includes a database; And if the efficiency of the wind power generator is less than or equal to a preset efficiency first threshold value, using the information on the database, based on the efficiency information of the wind power generator from the time when the wind power generator is installed to a time that becomes less than or equal to the first efficiency threshold value, Generates a generator efficiency approximation curve function, calculates a performance index for each part based on sensing data collected from the time when the wind turbine is installed to a time when the efficiency falls below the first threshold, and approximates the performance index for each part for the performance index A curve function is generated, and the wind power generator efficiency approximation curve function and part performance for each part from the point when the efficiency of the wind generator falls below the first efficiency threshold value to the point where the efficiency of the wind generator falls below the second efficiency threshold value. And a performance evaluation unit that evaluates the degree of similarity between the index approximation curve functions, and specifies, as a result of the similarity evaluation, a component having a component performance index approximation curve function whose similarity is equal to or greater than the reference similarity as a replacement target part.

Here, the replacement timing prediction unit may further include a replacement timing prediction unit for specifying a purchase/order timing of the replacement target component using the time required to obtain each component of the replacement target component.

In addition, the replacement timing prediction unit retroactively determines the time required to acquire the longest part among the replacement target parts from the time when the efficiency of the wind power generator reaches the second threshold. It can be specified as the timing of the purchase order of the planned parts.

In addition, the replacement timing prediction unit may specify a replacement target determined part among the replacement target parts when a specified replacement target part specific time is reached, which is a time point retroactively by a preset retroactive time from the purchase order scheduled time of the replacement target part. .

In addition, when the specified replacement target part is specified, the replacement timing prediction unit generates a wind power generator efficiency approximation curve function based on the efficiency information of the wind generator from the time when the wind generator is installed to the specified replacement target part, and the replacement target is scheduled. For each part, an approximate curve function of the performance index of the part from the time of installation of the wind generator to the specific point of the part to be replaced is generated, and the similarity of the approximate curve function of the wind power generator efficiency from the time from the specific point of the part to be replaced to the starting point of the confirmation of replacement construction A part having the above-described part performance index approximation curve function can be specified as a fixed part to be replaced.

In addition, it is possible to specify the time when the purchase order of the replacement target determined part is determined using the time required to obtain the replacement target determined part for each part for the replacement target determined part.

The present invention can optimize wind power generator maintenance support with a scheduling technique based on information collected from wind power generation.

1 is a functional block diagram of a Q&M platform device supporting maintenance of a scheduler-based wind power generator according to a preferred embodiment of the present invention.
2 is a diagram for describing a performance evaluation method of a performance evaluation unit of FIG. 1.
3 is a view for explaining the acquisition time and replacement construction time of the replacement target part.
FIG. 4 is a diagram illustrating a method of determining a replacement target part by a replacement timing prediction unit of FIG. 1.
FIG. 5 is a diagram for explaining a method in which the scheduler of FIG. 1 determines a part supply/demand period.
FIG. 6 is a diagram illustrating a method of determining a total replacement construction time by the scheduler of FIG. 1.
FIG. 7 is a diagram for explaining a method of determining a time for the scheduler of FIG. 1 to proceed with replacement construction among candidate replacement construction times.

In the present invention, various modifications may be made and various embodiments may be provided, and specific embodiments will be illustrated in the drawings and described in detail in the detailed description. However, this is not intended to limit the present invention to a specific embodiment, it is to be understood to include all changes, equivalents, or substitutes included in the spirit and scope of the present invention.

In describing each drawing, similar reference numerals have been used for similar elements. In describing the present invention, when it is determined that a detailed description of a related known technology may obscure the subject matter of the present invention, a detailed description thereof will be omitted.

Terms such as first and second may be used to describe various elements, but the elements should not be limited by the terms. These terms are used only for the purpose of distinguishing one component from another component.

For example, without departing from the scope of the present invention, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element.

The term and/or includes a combination of a plurality of related listed items or any of a plurality of related listed items.

The terms used in the present application are used only to describe specific embodiments, and are not intended to limit the present invention.

Singular expressions include plural expressions unless the context clearly indicates otherwise. In the present application, terms such as "comprise" or "have" are intended to designate the presence of features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, but one or more other features. It is to be understood that the presence or addition of elements or numbers, steps, actions, components, parts, or combinations thereof, does not preclude in advance.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs.

Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related technology, and should not be interpreted as an ideal or excessively formal meaning unless explicitly defined in this application. Does not.

Hereinafter, a scheduler-based wind power generation maintenance support Q&M platform device according to a preferred embodiment of the present invention will be described with reference to FIGS. 1 to 7. Hereinafter, in order to clarify the gist of the present invention, a description of conventionally well-known items is omitted or simplified.

Referring to FIG. 1, the Q&M platform device 10 includes a data collection unit 11, a database 12, a performance evaluation unit 13, a replacement timing prediction unit 14, a scheduler 15, and a power generation prediction unit ( 16), may include a maintenance resource management unit 17, a digital twin unit 18, and a Q&A unit 19.

The data collection unit 11 may collect sensing data from the wind turbine side. The sensing data may be sensing data for evaluating a component performance index of a wind generator to be monitored. In addition, the sensing data may be an external air factor that affects the amount of power generation of the wind power generator, for example, wind direction and wind speed. Parts of wind power generators that are to be monitored are blades, blade hubs, blade bearings, main shafts, generators, gear boxes, and disc brakes. Disk Brake), an oil cooler, a carbon shaft, a tower, and the like. To collect sensing data, various sensors such as a vibration sensor, a rotation detection sensor, a wind sensor, a wind direction sensor, and a current and voltage sensor may be used. For the maintenance target, for example, the items shown in the table below can be applied.

Category 1 Category 2 A Tower 02 Motor 04 Door & stair 05 Service lift 06 Main cable 07 Ladder 08 Platform 14 Cooling system 25 Sensors 27 Controller 29 Switch gear 30 Electrical part(Emergency) 31 Lightning system 34 Bolt tightening 37 Battery 38 Aviation light 44 AFFS B Hub 08 Platform 09 Nose cone 14 Cooling system 16 Brush 23 Rim 25 Sensors 27 Controller 30 Electrical part(Emergency) 31 Lightning system 34 Bolt tightening 35 Lubrication 37 Battery C Drive Train 01 Bearing 02 Motor 03 Pump 11 Torque arm 12 Oil flow 13 Wheels & stages 14 Cooling system 19 Manifold 21 Rotating union 25 Sensors 30 Electrical part(Emergency) 34 Bolt tightening 35 Lubrication 36 Rotor Disc 41 Coupling 42 Slipring 44 AFFS D Generator 01 Bearing 06 Main cable 13 Wheels & stages 14 Cooling system 16 Brush 17 Bus bar 25 Sensors 30 Electrical part(Emergency) 34 Bolt tightening 35 Lubrication 44 AFFS E Hydraulic system 02 Motor 03 Pump 12 Oil flow 15 Brake system 18 Valve & Switch 19 Manifold 20 Accumulator 25 Sensors 30 Electrical part(Emergency) 34 Bolt tightening 35 Lubrication F Yaw system 01 Bearing 02 Motor 15 Brake system 22 Gear 23 Rim 24 Yaw-Claw & Caliper 25 Sensors 26 EM brake 30 Electrical part(Emergency) 34 Bolt tightening 35 Lubrication G Pitch system 01 Bearing 02 Motor 20 Accumulator 22 Gear 23 Rim 25 Sensors 26 EM brake 30 Electrical part(Emergency) 34 Bolt tightening 35 Lubrication H Blade 01 Bearing 30 Electrical part(Emergency) 31 Lightning system 32 Internal(blade) 33 External(blade) 34 Bolt tightening 35 Lubrication I Nacelle 06 Main cable 08 Platform 10 Shaft 14 Cooling system 15 Brake system 25 Sensors 27 Controller 30 Electrical part(Emergency) 31 Lightning system 34 Bolt tightening 35 Lubrication 36 Rotor Disc 38 Aviation light 39 Anemometer 40 Windvane 44 AFFS J Power Control System
(TR,Converter) 06 Electrical part(Emergency) 14 Cooling system 17 Bolt tightening 25 Sensors 30 Bus bar 31 Main cable 34 Lightning system 44 AFFS

The database 12 may match and store the sensing data collected by the data collection unit 11 with time information. In addition, the database 12 may store a threshold value that is a criterion for determining a replacement timing for each component to be monitored. The threshold may be a component performance indicator. The threshold value may be a threshold value under a reference condition. Here, the reference condition may be a reference outside air condition, and the reference outside air condition may be a reference wind direction and a reference wind speed. In addition, the database 12 may store a reference power generation efficiency threshold. In addition, the database 12 may match and store power generation information with time information. In summary, the database 12 provides information necessary for the performance evaluation unit 13 to perform performance evaluation, information necessary for the replacement timing prediction unit 14 to predict the replacement timing, and the scheduler 15 to schedule the replacement timing. The information necessary for the power generation and the power generation amount prediction unit 16 may store and manage all of the information necessary to predict the power generation amount.

The performance evaluation unit 13 may evaluate the efficiency of the wind power generator by using the power generation amount information on the database 12. First, the performance evaluation unit 13 may calculate a theoretical amount of power generation of a wind power generator based on wind direction and wind speed information. In addition, the performance evaluation unit 13 determines whether the power generation amount information on the most recently updated database 12 is less than or equal to a preset ratio (THe1, hereinafter referred to as “efficiency first threshold”) of the theoretical power generation amount of the wind power generator. You can judge whether or not. Hereinafter, the efficiency of a wind power generator refers to a ratio of the sensed power generation amount of the wind power generator to the theoretical power generation amount of the wind power generator calculated based on wind direction and wind speed information. At this time, if it is determined that the power generation information on the most recently updated database 12 is less than or equal to the predetermined ratio THe1 of the theoretical wind power generation amount, the performance evaluation unit 13 provides the accumulated power generation amount information of the wind power generator so far. It is possible to predict when the wind power generator replacement construction should be started based on the amount of power generated by the wind power generator. The theoretical power generation amount of the wind power generator may be calculated by wind direction and wind speed information acquired at the same time as the power generation amount information on the database 12 that was most recently updated.

Referring to FIG. 2, the performance evaluation unit 13 may recognize that the efficiency of the power generation amount of the wind power generation updated in the database at the time T1 is less than or equal to the first efficiency threshold THe1. At this time, the performance evaluation unit 13 is based on the wind power generator efficiency approximation curve function based on the efficiency information of the wind power generator from the time when the wind power generator is installed (t=0) to the time T1 that becomes less than or equal to the first efficiency threshold value THe1. Can be created. At this time, an approximate efficiency curve function is generated by inducing an approximate nonlinear function using the efficiency of the wind generator from the time when the wind power generator is installed (t=0) to the time when it becomes less than the first efficiency threshold THe1 (T1). I can. The efficiency threshold value for determining whether to replace the wind generator parts based on the efficiency of the wind generator may be the second efficiency threshold THe2. The second efficiency threshold THe2 may be 80%. In FIG. 2, the wind generator efficiency approximation curve function may be less than or equal to the second efficiency threshold at a time point T3.

The performance evaluation unit 13 includes a time point T3 when the efficiency of the wind power generator becomes less than or equal to the second efficiency threshold value THe2 at a time point T1 when the efficiency of the wind power generator is less than or equal to the first efficiency threshold value THe1 among various parts constituting the wind power generator. It is possible to search for parts that show a degradation pattern similar to the efficiency approximation curve function up to ).

To this end, the performance evaluation unit 13 calculates a performance index for each part based on the sensing data collected from the time when the wind power generator is installed (t=0) to the time when it becomes less than the first efficiency threshold (THe1) (T1), and In addition, it is possible to generate an approximate curve function for each part performance index for the performance index.

In addition, the performance evaluation unit 13 is from a time point T1 when the efficiency of the wind power generator becomes less than or equal to the first efficiency threshold value THe1 to a time point T3 when the efficiency of the wind power generator becomes less than or equal to the second efficiency threshold value THe1. Until, it is possible to evaluate the similarity between the wind generator efficiency approximation curve function and the component performance index approximation curve function for each part.

At this time, the performance evaluation unit 13 is the average of the difference between the efficiency reduction rate on the wind generator efficiency approximation curve function for each preset section and the performance degradation rate on the component performance index approximation curve function is less than or equal to a preset average difference (for example, 10%). In this case, the degree of similarity can be evaluated as higher than the standard similarity.

The performance evaluation unit 13 may specify a part having a part performance index approximation curve function whose similarity of the wind generator efficiency approximation curve function is equal to or greater than the reference similarity as a replacement target part.

2 illustrates a case in which parts 1, 2, and 3 have a part performance index approximation curve function that exceeds a reference similarity compared to the wind generator efficiency approximation curve function. That is, the case where the replacement target part is parts 1 to 3. In this way, by extracting the replacement target part based on the correlation with the generator efficiency, a part replacement plan optimized for the efficiency of the system may be established.

In FIG. 2, a1 may be a time required to obtain part 1 and b1 may indicate a time required for replacement of part 1. In FIG. 2, a2 may indicate a time required to obtain part 2 and b2 may indicate a time required for replacement of part 2. In FIG. 3, a3 may indicate a time required to obtain part 3 and b3 may indicate a time required for replacement work of part 3. As will be described later, the time required to obtain each part and the time required for the replacement construction may be managed by the maintenance resource management unit 17.

Referring to FIG. 2, the time required for obtaining the part and the time required for the replacement construction may be different depending on the replacement target part. The performance evaluation unit 13 may specify a time point T3 at which the efficiency of the wind power generator is the second threshold value THe2 as a scheduled start point for replacement construction.

The replacement timing prediction unit 14 may specify a purchase order timing (Tdue) of a replacement target part by using the time required to acquire each part of the replacement target part. Referring to FIG. 3, the replacement timing prediction unit 14 places an order to purchase replacement target parts in order to obtain all of the replacement target parts at a time (T3) when the efficiency of the wind power generator reaches the second threshold value THe2. It is possible to specify the closing point of the purchase order period for parts to be made. At this time, the closing time of the part purchase order period is from the time when the efficiency of the wind power generator reaches the second threshold (THe2) (T3) and the time required to obtain the longest part among the scheduled parts to be replaced. May be retroactive. The replacement timing prediction unit 14 may specify the closing time of the part purchase order period as the purchase order timing (Tdue) of the part to be replaced.

The replacement timing prediction unit 14 may determine the replacement target part, among the replacement target parts, before the purchase order timing (Tdue) of the replacement target part. To this end, the replacement timing prediction unit 14 is referred to as a time point retroactively by a preset retroactive time (Δt) from the scheduled purchase order time (Tdue) of the part to be replaced (Ttem, hereinafter, referred to as “specified time for the determined part to be replaced”. ), it is possible to specify the part to be replaced among the parts to be replaced.

Referring to FIG. 4, as previously seen, a replacement target part may be specified at a time point T1.

When the specified replacement target part specific time (Ttem) comes, the replacement timing prediction unit 14 is based on the efficiency information of the wind power generator from the installation time of the wind generator (t=0) to the specific replacement target part (t=Ttem). Thus, the approximate curve function of the wind power generator efficiency can be generated. In addition, for each part to be replaced, a component performance index approximation curve function may be generated from the time when the wind power generator is installed (t=0) to the specific time point of the replacement target determined part (t=Ttem). Here, the method of generating the wind turbine efficiency approximation curve function and the component performance index approximation curve function is as described above. Hereinafter, on the wind generator efficiency approximation curve function generated by the replacement timing prediction unit 14 based on the efficiency information of the wind power generator from the time when the wind power generator is installed (t=0) to the specific time point of the part to be replaced (t=Ttem). , The time point T3' when the efficiency becomes less than or equal to the second threshold value THe2 is referred to as a “replacement work confirmation start point”.

At this time, the replacement timing prediction unit 14 is a component performance index approximation curve whose wind power generator efficiency approximation curve function similarity is greater than or equal to the reference similarity from the time from the specific time point of the part to be replaced (t=Ttem) to the start point (T3') A part having a function can be specified as a fixed part to be replaced. The matters for determining the similarity between the wind generator efficiency approximation curve function and the component performance index approximation curve function are as previously described. Referring to FIG. 5, it can be seen that part 1 is included in the replacement target part, but is excluded from the replacement target determined part. In other words, it can be seen that more reliable results can be obtained for the parts to be replaced than in T1 with the data accumulated up to a specific point in time (Ttem) of the parts to be replaced.Through this, it is possible to minimize unnecessary parts replacement based on predictability. I can. Since the variable used to generate the approximate curve function is added compared to FIG. 2 in FIGS. 4 and 5, the viewpoints of T3 of FIG. 2 and T3′ of FIGS. 4 and 5 may be different.

The scheduler 15 may specify a purchase order confirmation point (Tdue') of the determined part to be replaced by using the time required to acquire the part to be replaced with respect to the determined part to be replaced. The purchase order confirmation time (Tdue') of the target confirmed part may be a time point retroactively as much as the time required to acquire the part that takes the longest time to acquire among the confirmed parts to be replaced from the replacement construction confirmation start point (T3').

The scheduler 15 may determine the entire replacement construction time. 6 illustrates that, for convenience of description, parts 1, 2, and 3 are determined parts to be replaced.

Referring to FIG. 6, the scheduler 15 may arrange the replacement construction time for each part in the order of long replacement construction time. At this time, replacement work for each part can be done in parallel with other parts replacement work, or it may not be possible. In order to distinguish this, the maintenance resource management unit 17 may manage whether other parts replacement work and the corresponding parts replacement work can be concurrently performed for each part as attribute information of parts.

The scheduler 15 can rearrange the replacement construction time. At this time, the scheduler 15 sequentially starts with the parts with the second priority in the replacement construction time ranking, and if the replacement construction time of all parts with the highest replacement construction time ranking and the replacement construction time subject to rearrangement can be overlapped, The earliest starting point among the starting points of the priority replacement construction time is the starting point of the replacement construction target for rearrangement, and there is at least one replacement construction that cannot overlap the replacement construction time of the replacement target during the replacement construction period of parts with the highest priority for replacement construction time. If present, the slowest end point among the top-ranked replacement construction time end points that cannot be overlapped may be used as the replacement construction start point. Figure 2 illustrates a case where the replacement work of part 2 can overlap with the replacement work of part 1, and the replacement work of part 3 can overlap with the replacement work of part 1, but it is not possible to overlap with the replacement work of part 2 do.

When rearrangement of the replacement construction time is completed in this way, the scheduler 15 can determine the time from the earliest starting point of the replacement construction time to the slowest ending point of the replacement construction time as the total replacement construction time (btotal). have.

The scheduler 15 may set a replacement construction candidate period using the replacement construction determination starting point T3' as a starting point. The replacement construction candidate period may be a preset multiple (eg, 1.5 times) of the total replacement construction time (btotal). The power generation predicting unit 16 may predict the amount of power generation of the wind power generator during the replacement construction candidate period based on past weather information and predicted weather information.

The scheduler 15 sets the starting point of the entire replacement construction time as the replacement construction confirmation starting point (T3'), and shifts the entire replacement construction time within the replacement construction candidate period, while the predicted wind power generation amount belongs to the smallest section. The total replacement construction time can be specified. And, the specified total replacement construction time may be determined as the total replacement construction time. Accordingly, power generation loss due to the replacement work can be minimized.

As described above, the maintenance resource management unit 17 may manage time required for acquisition of each part, time required for replacement construction, replacement construction cost, inventory parts, and the like. The maintenance resource management unit 17 may provide an interface through which a component supplier and a component replacement construction company can upload corresponding information. The maintenance resource management unit 17 may manage, for each part, whether other parts replacement work and the corresponding part replacement work can be concurrently performed as part attribute information.

The digital twin unit 18 displays the performance evaluation result of the performance evaluation unit 13, the replacement timing prediction result of the replacement timing prediction unit 14, and the replacement construction scheduling result of the scheduler 15 on the wind turbine modeled in 3D. can do.

The Q&M unit 19 will provide the performance evaluation result of the performance evaluation unit 13, the replacement timing prediction result of the replacement time prediction unit 14, and the replacement construction scheduling result of the scheduler 15 in a Q&M method according to the user's request. I can.

Based on the generator efficiency, estimate the purchase order timing (Tdue) and the scheduled start point of replacement construction (T3) of the part to be replaced, and specify the part to be replaced at the specific time (Ttem) of the part to be replaced. By specifying the purchase order confirmation point (Tdue') and the replacement construction confirmation start point (T3'), the scheduling of the replacement work may be more accurate and accurate wind power generator asset management may be possible.

10: Q&M platform device
11: data collection unit
12: database
13: performance evaluation unit
14: replacement timing prediction unit
15: scheduler
16: generation amount prediction unit
17: Maintenance Resource Management Department
18: Digital Twin Section
19: Q&A department

Claims (6)

database; And
Using the information on the database, if the efficiency of the wind power generator is less than or equal to a preset efficiency first threshold value, the wind power generator is based on the efficiency information of the wind power generator from the time of installation of the wind power generator to the time that it becomes less than or equal to the first efficiency threshold. An efficiency approximation curve function is generated, a performance index for each part is calculated based on the sensing data collected from the time when the wind turbine is installed to a time when the efficiency becomes less than or equal to the first threshold value, and a part performance index approximation curve for the performance index From the time when the function is generated and the efficiency of the wind power generator falls below the first efficiency threshold value to the point when the efficiency of the wind generator falls below the second efficiency threshold value, the wind generator efficiency approximation curve function and the component performance index for each part Supports maintenance of a scheduler-based wind power generator including a performance evaluation unit that evaluates the similarity between approximate curve functions, and specifies a part with an approximate curve function as a replacement target part, as a result of the similarity evaluation, a component performance index with a similarity greater than or equal to the reference similarity Q&M platform device. The method of claim 1,
A Q&M platform device for maintenance support for wind turbines based on a scheduler, which further includes a replacement timing prediction unit that specifies when the replacement target parts are scheduled to be purchased and ordered using the time required to obtain each part. The method of claim 2,
The replacement timing prediction unit retroactively measures the time required to acquire the longest part among the replacement target parts from the time when the efficiency of the wind generator reaches the second threshold. Q&M platform device that supports maintenance of a scheduler-based wind power generator, characterized in that it specifies the timing of the purchase order of The method of claim 3,
The replacement timing prediction unit is characterized in that when a specific time point for the determined part to be replaced, which is a time point retroactively by a preset retroactive time from the time when the part to be replaced is scheduled to be purchased and ordered, is to specify the part to be replaced among the parts to be replaced. A Q&M platform device that supports maintenance of a scheduler-based wind generator. The method of claim 4,
When the specified replacement target part is at a specific time, the replacement timing prediction unit generates a wind power generator efficiency approximation curve function based on the efficiency information of the wind power generator from the time when the wind power generator is installed to the specific replacement target part, and Parts whose performance index approximation curve function is generated from the time of installation of the wind generator to the specified part to be replaced, and the approximate curve function of the wind power generator efficiency from the time from the specified time to the starting point of the confirmation of the replacement construction is greater than the standard similarity A Q&M platform device that supports maintenance of a wind power generator based on a scheduler, characterized in that a part having a performance index approximation curve function is specified as a replacement target determined part. The method of claim 5,
A scheduler-based maintenance support Q&M platform device for a wind generator based on a scheduler, characterized in that the time required to obtain a replacement target determined part for each part for a replacement target determined part is specified when the purchase order is confirmed.

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