CN115270326A - System and method for prolonging service life of main speed-increasing gear box of wind turbine generator - Google Patents
System and method for prolonging service life of main speed-increasing gear box of wind turbine generator Download PDFInfo
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Abstract
The invention relates to the technical field of wind turbine generators, in particular to a system and a method for prolonging the service life of a main speed-increasing gear box of a wind turbine generator. The method specifically comprises the following steps: acquiring a plurality of groups of historical wind turbine generator gearbox operation data, and establishing a wind turbine generator service life prediction model; acquiring real-time image data of a wind turbine generator gearbox, generating a first estimated service life value of the wind turbine generator, and judging whether to repair the wind turbine generator according to the surface loss grade of the wind turbine generator; and acquiring the repaired wind turbine generator gearbox image data, generating a second estimated service life value of the wind turbine generator, and judging whether compensation repair is performed or not. The residual service life of the gearbox of the unit can be accurately estimated. The service life of the existing running unit gear box can be diagnosed, and the remaining service life can be estimated. And based on the above, a maintenance scheme is made and implemented. And finally, evaluating and comparing the maintenance effect. The online maintenance of the gear box is realized, and the service life of the gear box is prolonged.
Description
Technical Field
The invention relates to the technical field of wind turbine generators, in particular to a system and a method for prolonging the service life of a main speed-increasing gear box of a wind turbine generator.
Background
With the rapid development of the wind power generation industry in China, the number of the wind power plants put into production in China is the first place in the world. By 2019, the cumulative installed capacity of wind power of Huaneng group is nearly 1996 ten thousand kilowatts, and the number of units exceeds 10000. The wind power capacity put into production in China reaches 209.53GW (wind energy Special committee CWEA, china wind power hoisting capacity statistics briefing in 2018, published in 2019 in 4 months and 4 days), is the first place in the world and far exceeds the second United states 96.4GW. The wind turbine generators put into operation by Huaneng group have more than 300 gear boxes each year and need to be offline for maintenance, and the maintenance cost of the traditional mode is huge.
The failure of the speed increasing gear box of the unit causes shutdown and offline maintenance, thereby causing great economic loss on site. Conventional measures, such as regular replacement of designated lubricating oil, replacement of filter elements, etc., do not solve the problem of continued wear development. Furthermore, in recent years, maintenance data has shown that the number of times of offline maintenance of the gear of the gearbox due to a failure is increasing. Statistically, an average of 1 gearbox, and up to 4, is replaced per wind farm per year. The proportion is from 3 percent to 10 percent. In the traditional maintenance mode, the whole or part of the gearbox needs to be disassembled, replaced and maintained by large-scale hoisting equipment in a shutdown state. And the replacement cost of each gear box exceeds 150 million RMB.
Disclosure of Invention
The purpose of the invention is: in order to prolong the service life of the gearbox on line and greatly reduce the problem of cost rise caused by off-line maintenance of the gearbox, the invention provides a method for prolonging the service life of a main speed-increasing gearbox of a wind turbine generator.
In some embodiments of the application, the characteristic values of the surface morphology are extracted after preprocessing by acquiring image information of the surfaces of the newly built gear box, the fault gear box and the gear of the operated gear box of the related wind turbine generator. And (3) by combining the collected accumulated operation hours, accumulated power generation, the service time of the gear box, the fault operation hours and the like of the unit, deep learning is carried out by utilizing an artificial intelligence technology, and an intelligent model of the surface form and the service time is established. The verified mathematical model can accurately estimate the residual service life of the unit gearbox.
In some embodiments of the present application, the repaired gear surface morphology image is analyzed using the established intelligent model to calculate the remaining service life of the gearbox after online repair. And comparing the surface data of the gear box before repair, and evaluating the online maintenance effect and the running state of the gear box.
In some embodiments of the present application, a method for prolonging a service life of a main speed-increasing gearbox of a wind turbine generator system is provided, which includes:
the method comprises the following steps: acquiring a plurality of groups of historical wind turbine generator gearbox operation data, and establishing a wind turbine generator service life prediction model;
step two: acquiring real-time image data of a gear box of the wind turbine generator, generating a first estimated service life value of the wind turbine generator, and judging whether to repair the gear box according to the surface loss grade of the wind turbine generator;
step three: and acquiring the repaired wind turbine generator gearbox image data, generating a second estimated service life value of the wind turbine generator, and judging whether compensation repair is performed or not.
In some embodiments of the present application, the obtaining of the number of operations of the gear box of the plurality of groups of historical wind turbine generators specifically includes:
acquiring image information of the surfaces of a newly-built gear box, a fault gear box and a gear of an operated gear box of a wind turbine generator, acquiring a characteristic value of a surface form and generating surface form historical data;
acquiring data of accumulated operation hours, accumulated power generation, use time of a gear box and fault operation hours of a unit to generate operation historical data;
and establishing a wind turbine generator service life prediction model according to the surface form historical data and the operation historical data.
In some embodiments of the present application, the second step specifically is:
presetting a wind turbine surface loss grade matrix A, and setting A (A1, A2, A3, A4), wherein A1 is a first preset wind turbine surface loss grade, A2 is a second preset wind turbine surface loss grade, A3 is a third preset wind turbine surface loss grade, A4 is a fourth preset wind turbine surface loss grade, and A1 is more than A2 and less than A3 and less than A4;
presetting a repairing agent dosage matrix B, and setting B (B1, B2, B3, B4), wherein B1 is a first preset repairing agent dosage, B2 is a second preset repairing agent dosage, B3 is a third preset repairing agent dosage, B4 is a fourth preset repairing agent dosage, and B1 is more than B2, more than B3 and less than B4;
generating a wind turbine surface loss grade a according to real-time operation data of the wind turbine acquired in real time, and setting a real-time repairing agent dosage B according to the relation between a wind turbine surface loss grade matrix A and a repairing agent dosage matrix B, wherein the method specifically comprises the following steps:
when the wind turbine surface loss grade a is between a first preset wind turbine surface loss grade A1 and a second preset wind turbine surface loss grade A2, setting a first preset repairing agent dosage B1 as a real-time repairing agent dosage, namely B = B1;
when the wind turbine surface loss grade a is between a second preset wind turbine surface loss grade A2 and a third preset wind turbine surface loss grade A3, setting a second preset repairing agent dosage B2 as a real-time repairing agent dosage, namely B = B2;
when the wind turbine surface loss level a is between a third preset wind turbine surface loss level A3 and a fourth preset wind turbine surface loss level A4, setting a third preset repairing agent dosage B3 as a real-time repairing agent dosage, namely B = B3;
and when the wind turbine surface loss grade a is larger than a fourth preset wind turbine surface loss grade A4, setting a fourth preset repairing agent dosage B4 as a real-time repairing agent dosage, namely B = B4.
In some embodiments of the present application, the third step includes:
generating a repairing difference value according to the second predicted service life value of the wind turbine generator and the first preset service life value of the wind turbine generator;
and judging whether to perform compensation repair according to the repair difference value.
In some embodiments of the present application, the determining whether to perform compensation repair according to the repair difference includes:
presetting a compensation coefficient matrix C, and setting C (C1, C2, C3, C4), wherein C1 is a first preset compensation coefficient, C2 is a second preset compensation coefficient, C3 is a third preset compensation coefficient, C4 is a fourth preset compensation coefficient, and C1 is greater than 0, C2 is greater than C3, and C4 is greater than 0.3;
presetting a restoration difference matrix D, and setting D (D1, D2, D3, D4), wherein D1 is a preset first restoration difference, D2 is a preset second restoration difference, D3 is a third preset restoration difference, D4 is a fourth preset restoration difference, and D1 is greater than D2 and less than D3 and less than D4;
acquiring a restoration difference D, and selecting a compensation coefficient c according to the relation between the real-time restoration difference D and a preset restoration difference matrix D so as to compensate and restore the wind turbine generator gearbox:
when the restoration difference value c is between a preset fourth restoration difference value D4 and a preset third restoration difference value D3, selecting a first preset compensation coefficient c1 to compensate the i-th preset restoration agent dosage Bi, wherein the compensation restoration agent dosage of the wind turbine gearbox is c1 Bi;
when the restoration difference value c is between a preset third restoration difference value D3 and a preset second restoration difference value D2, selecting a second preset compensation coefficient c2 to compensate the i-th preset restoration agent dosage Bi, wherein the compensation restoration agent dosage of the wind turbine generator gearbox is c2 Bi;
when the restoration difference value c is between a preset second restoration difference value D2 and a preset first restoration difference value D1, selecting a third preset compensation coefficient c3 to compensate the i-th preset restoration agent dosage Bi, wherein the compensation restoration agent dosage of the wind turbine gearbox is c3 Bi;
and when the restoration difference value c is lower than a preset first restoration difference value D1, selecting a first preset compensation coefficient c4 to compensate the ith preset restoration agent dosage Bi, wherein the compensation restoration agent dosage of the wind turbine generator gearbox is c4 Bi.
In some embodiments of the present application, a system for extending the service life of a main gearbox of a wind turbine generator is provided, comprising:
the monitoring unit is used for acquiring historical operating data of a gearbox of the wind turbine generator and establishing a service life prediction model of the wind turbine generator;
the image acquisition unit is connected with the monitoring unit through a wireless signal and is used for acquiring real-time image data of the surface of a gear of the operating gear box;
and the data processing unit is connected with the monitoring unit through a wireless signal, and the image acquisition unit is used for processing the image information of the surface of the gear of the operating gear box acquired by the image acquisition unit and generating a repair instruction.
In some embodiments of the present application, the monitoring unit comprises:
the operation monitoring module is used for acquiring data of the accumulated operation hours, the accumulated power generation amount, the use time of the gear box and the fault operation hours of the unit and generating operation historical data;
and the image monitoring module is used for acquiring the image information of the surfaces of the newly-built gear box, the fault gear box and the gear of the operated gear box of the wind turbine generator, acquiring the characteristic value of the surface morphology and generating historical data of the surface morphology.
In some embodiments of the present application, the monitoring unit further comprises:
and the central module is used for acquiring surface form historical data and operation historical data and establishing a service life prediction model of the wind turbine generator.
In some embodiments of the present application, the data processing unit includes:
the image information processing module is used for acquiring real-time image data of the surface of the gear of the operating gearbox and generating a characteristic value of a real-time surface form;
the first prediction module is used for acquiring a characteristic value of a real-time surface form and generating a first predicted service life value according to a life prediction model;
the first evaluation module is used for generating the surface loss grade of the wind turbine generator according to the characteristic value of the real-time surface form;
and the first repairing module is used for setting the using amount of a repairing agent according to the surface loss grade of the wind turbine generator.
In some embodiments of the present application, the data processing unit further comprises:
the second prediction module is used for acquiring the repaired surface morphology characteristic value and generating a second predicted service life value according to the service life prediction model;
the difference module generates a repair difference according to the first estimated service life value and the second estimated service life value;
the second restoration module judges whether to carry out compensation restoration according to the restoration difference value
Compared with the prior art, the method for prolonging the service life of the main speed-increasing gear box of the wind turbine generator has the following beneficial effects:
by establishing a predictive model of surface morphology versus time of use. The residual service life of the gearbox of the unit can be accurately estimated. By taking the prediction model as a core, the service life of the existing running unit gear box can be diagnosed, and the remaining service life can be predicted. And based on the maintenance plan, the maintenance plan is made and implemented. And finally, evaluating and comparing the maintenance effect. The online maintenance of the gear box is realized, and the service life of the gear box is prolonged.
Drawings
FIG. 1 is a schematic flow chart of a method for prolonging the service life of a main speed-increasing gearbox of a wind turbine generator system in an embodiment of the invention;
FIG. 2 is a schematic structural diagram of a system for prolonging the service life of a main speed-increasing gearbox of a wind turbine generator system in an embodiment of the invention.
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
In the description of the present application, it is to be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like indicate orientations or positional relationships based on those shown in the drawings, merely for convenience of description and simplicity of description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed in a particular orientation, and be operated, and thus, are not to be construed as limiting the present application.
The terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present application, "a plurality" means two or more unless otherwise specified.
In the description of the present application, it should be noted that, unless otherwise explicitly stated or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, a fixed connection, a detachable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present application can be understood in a specific case by those of ordinary skill in the art.
As shown in fig. 1, a method for prolonging a service life of a main speed-increasing gearbox of a wind turbine generator according to a preferred embodiment of the present invention includes:
the method comprises the following steps: acquiring a plurality of groups of historical wind turbine generator gearbox operation data, and establishing a wind turbine generator service life prediction model;
step two: acquiring real-time image data of a wind turbine generator gearbox, generating a first estimated service life value of the wind turbine generator, and judging whether to repair the wind turbine generator according to the surface loss grade of the wind turbine generator;
step three: and acquiring the repaired wind turbine generator gearbox image data, generating a second estimated service life value of the wind turbine generator, and judging whether compensation repair is performed or not.
Specifically, the method for acquiring the operation number of the gear boxes of the historical wind turbine generators specifically comprises the following steps:
acquiring image information of the surfaces of a newly built gear box, a fault gear box and a gear of an operated gear box of a wind turbine generator, acquiring a characteristic value of a surface form and generating historical data of the surface form;
acquiring data of accumulated operation hours, accumulated power generation, gear box service time and fault operation hours of a unit to generate operation historical data;
and establishing a wind turbine generator service life prediction model according to the surface form historical data and the operation historical data.
Specifically, an artificial intelligence technology is utilized to enter deep learning, and an intelligent model of the surface morphology and the service time is established. The verified mathematical model can accurately estimate the residual service life of the unit gearbox.
In some preferred embodiments of the present application, step two is specifically:
presetting a wind turbine surface loss grade matrix A, and setting A (A1, A2, A3, A4), wherein A1 is a first preset wind turbine surface loss grade, A2 is a second preset wind turbine surface loss grade, A3 is a third preset wind turbine surface loss grade, A4 is a fourth preset wind turbine surface loss grade, and A1 is more than A2 and less than A3 and less than A4;
presetting a repairing agent dosage matrix B, and setting B (B1, B2, B3, B4), wherein B1 is a first preset repairing agent dosage, B2 is a second preset repairing agent dosage, B3 is a third preset repairing agent dosage, B4 is a fourth preset repairing agent dosage, and B1 is more than B2 and more than B3 and less than B4;
generating a wind turbine surface loss grade a according to real-time operation data of the wind turbine acquired in real time, and setting a real-time repairing agent dosage B according to the relation between a wind turbine surface loss grade matrix A and a repairing agent dosage matrix B, wherein the method specifically comprises the following steps:
when the wind turbine surface loss level a is between a first preset wind turbine surface loss level A1 and a second preset wind turbine surface loss level A2, setting a first preset repairing agent dosage B1 as a real-time repairing agent dosage, namely B = B1;
when the wind turbine surface loss grade a is between a second preset wind turbine surface loss grade A2 and a third preset wind turbine surface loss grade A3, setting a second preset repairing agent dosage B2 as a real-time repairing agent dosage, namely B = B2;
when the wind turbine surface loss level a is between a third preset wind turbine surface loss level A3 and a fourth preset wind turbine surface loss level A4, setting a third preset repairing agent dosage B3 as a real-time repairing agent dosage, namely B = B3;
and when the wind turbine surface loss grade a is larger than a fourth preset wind turbine surface loss grade A4, setting a fourth preset repairing agent dosage B4 as a real-time repairing agent dosage, namely B = B4.
Specifically, the online abrasion repairing technology is adopted, and the repairing material is manually and directly coated on the surface of the gear in the form of a repairing agent.
It can be understood that, in the above embodiment, the real-time repairing agent dosage is set according to the relationship between the wind turbine surface loss grade matrix and the repairing agent dosage matrix, so that the repairing efficiency is improved, and the repairing time is shortened to realize accurate repairing.
In some preferred embodiments of the present application, step three comprises:
generating a restoration difference value according to the second predicted service life value of the wind turbine generator and the first preset service life value of the wind turbine generator;
and judging whether to perform compensation repair according to the repair difference value.
Specifically, judging whether to perform compensation restoration according to the restoration difference value comprises:
presetting a compensation coefficient matrix C, and setting C (C1, C2, C3, C4), wherein C1 is a first preset compensation coefficient, C2 is a second preset compensation coefficient, C3 is a third preset compensation coefficient, C4 is a fourth preset compensation coefficient, and C1 is greater than 0, C2 is greater than C3, and C4 is greater than 0.3;
presetting a restoration difference matrix D, and setting D (D1, D2, D3, D4), wherein D1 is a preset first restoration difference, D2 is a preset second restoration difference, D3 is a third preset restoration difference, D4 is a fourth preset restoration difference, and D1 is greater than D2 and less than D3 and less than D4;
acquiring a repairing difference D, and selecting a compensation coefficient c according to the relation between the real-time repairing difference D and a preset repairing difference matrix D so as to compensate and repair the wind turbine gearbox:
when the restoration difference value c is between a preset fourth restoration difference value D4 and a preset third restoration difference value D3, a first preset compensation coefficient c1 is selected to compensate the ith preset restoration agent dosage Bi, and the compensation restoration agent dosage of the wind turbine generator gearbox is c1 Bi;
when the restoration difference value c is between a preset third restoration difference value D3 and a preset second restoration difference value D2, selecting a second preset compensation coefficient c2 to compensate the ith preset restoration agent dosage Bi, wherein the compensation restoration agent dosage of the wind turbine generator gearbox is c2 Bi;
when the restoration difference value c is between a preset second restoration difference value D2 and a preset first restoration difference value D1, selecting a third preset compensation coefficient c3 to compensate the ith preset restoration agent dosage Bi, wherein the compensation restoration agent dosage of the wind turbine generator gearbox is c3 Bi;
and when the restoration difference value c is lower than a preset first restoration difference value D1, selecting a first preset compensation coefficient c4 to compensate the ith preset restoration agent dosage Bi, wherein the compensation restoration agent dosage of the wind turbine generator gearbox is c4 Bi.
It can be understood that, in the above embodiment, whether compensation repair is performed is judged according to the repair difference, and a compensation coefficient is selected according to a relationship between the repair difference and a preset repair difference matrix, so as to suppress the generation of pitting corrosion and achieve the purpose of controlling the wear of the gearbox. The service life of the gearbox on line is prolonged, and the cost rise caused by off-line maintenance of the gearbox is greatly reduced.
In some preferred embodiments of the present application, according to the method in the above embodiments, there is provided a system for prolonging the service life of a main speed-increasing gearbox of a wind turbine generator, comprising:
the monitoring unit is used for acquiring historical operating data of a gearbox of the wind turbine generator and establishing a service life prediction model of the wind turbine generator;
the image acquisition unit is connected with the monitoring unit through a wireless signal and is used for acquiring real-time image data of the surface of the gear of the operating gear box;
and the data processing unit is connected with the monitoring unit through a wireless signal, and the image acquisition unit is used for processing the image information of the surface of the gear of the operating gear box acquired by the image acquisition unit and generating a repairing instruction.
Particularly, the image acquisition unit is an endoscope, can conveniently acquire the surface state of the gear, can reflect the wear state of the gear, and has low detection cost.
Specifically, the monitoring unit collects at least 3 wind power plants, the gearbox data of more than 100 units are collected, and a mathematical model is established through an artificial intelligence method. The model can accurately reflect the relationship between the wear form and the service life of the gearbox.
Specifically, the monitoring unit includes:
the operation monitoring module is used for acquiring data of the accumulated operation hours, the accumulated power generation amount, the use time of the gear box and the fault operation hours of the unit and generating operation historical data;
and the image monitoring module is used for acquiring image information of the surfaces of a newly-built gear box, a fault gear box and a gear of an operated gear box of the wind turbine generator, acquiring characteristic values of surface morphology and generating historical data of the surface morphology.
Specifically, the monitoring unit further includes:
and the central module is used for acquiring surface form historical data and operation historical data and establishing a service life prediction model of the wind turbine generator.
Specifically, the data processing unit includes:
the image information processing module is used for acquiring real-time image data of the surface of the gear of the operating gearbox and generating a characteristic value of a real-time surface form;
the first prediction module is used for acquiring a characteristic value of a real-time surface form and generating a first predicted service life value according to the life prediction model;
the first evaluation module is used for generating the surface loss grade of the wind turbine generator according to the characteristic value of the real-time surface form;
and the first repairing module is used for setting the using amount of a repairing agent according to the surface loss grade of the wind turbine generator.
Specifically, the data processing unit further includes:
the second prediction module is used for acquiring the repaired surface morphology characteristic value and generating a second predicted service life value according to the service life prediction model;
the difference module generates a repair difference according to the first estimated service life value and the second estimated service life value;
and the second repairing module judges whether to perform compensation repairing according to the repairing difference value.
According to the first concept of the application, the characteristic values of the surface morphology are extracted after preprocessing by acquiring the image information of the surfaces of the newly built gear box, the fault gear box and the gear of the operated gear box of the related wind turbine generator. And (4) by combining the collected accumulated running hours, accumulated generating capacity, the using time of the gear box, the fault running hours and the like of the unit, deep learning is carried out by utilizing an artificial intelligence technology, and an intelligent model of the surface form and the using time is established. The verified mathematical model can accurately estimate the residual service life of the unit gearbox.
According to the second concept of the application, the repaired gear surface morphology image is analyzed by utilizing the established intelligent model, and the remaining service life of the gear box after on-line repair is calculated. And comparing the surface data of the gear box before repair, and evaluating the online maintenance effect and the running state of the gear box.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, many modifications and substitutions can be made without departing from the technical principle of the present invention, and these modifications and substitutions should also be regarded as the protection scope of the present invention.
Claims (10)
1. A method for prolonging the service life of a main speed-increasing gear box of a wind turbine generator is characterized by comprising the following steps:
the method comprises the following steps: acquiring a plurality of groups of historical wind turbine generator gearbox operation data, and establishing a wind turbine generator service life prediction model;
step two: acquiring real-time image data of a gear box of the wind turbine generator, generating a first estimated service life value of the wind turbine generator, and judging whether to repair the gear box according to the surface loss grade of the wind turbine generator;
step three: and acquiring the repaired wind turbine generator gearbox image data, generating a second estimated service life value of the wind turbine generator, and judging whether compensation repair is performed or not.
2. The method for prolonging the service life of the main speed-increasing gearbox of the wind turbine generator set according to claim 1, wherein the obtaining of the operation number of the plurality of groups of historical wind turbine generator set gearboxes specifically comprises:
acquiring image information of the surfaces of a newly built gear box, a fault gear box and a gear of an operated gear box of a wind turbine generator, acquiring a characteristic value of a surface form and generating historical data of the surface form;
acquiring data of accumulated operation hours, accumulated power generation, use time of a gear box and fault operation hours of a unit to generate operation historical data;
and establishing a wind turbine generator service life prediction model according to the surface form historical data and the operation historical data.
3. The method for prolonging the service life of the main speed increasing gearbox of the wind turbine generator set according to claim 2, wherein the second step is specifically as follows:
presetting a wind turbine surface loss grade matrix A, and setting A (A1, A2, A3, A4), wherein A1 is a first preset wind turbine surface loss grade, A2 is a second preset wind turbine surface loss grade, A3 is a third preset wind turbine surface loss grade, A4 is a fourth preset wind turbine surface loss grade, and A1 is more than A2 and less than A3 and less than A4;
presetting a repairing agent dosage matrix B, and setting B (B1, B2, B3, B4), wherein B1 is a first preset repairing agent dosage, B2 is a second preset repairing agent dosage, B3 is a third preset repairing agent dosage, B4 is a fourth preset repairing agent dosage, and B1 is more than B2, more than B3 and less than B4;
generating a wind turbine surface loss grade a according to real-time operation data of the wind turbine acquired in real time, and setting a real-time repairing agent dosage B according to the relation between a wind turbine surface loss grade matrix A and a repairing agent dosage matrix B, wherein the method specifically comprises the following steps:
when the wind turbine surface loss level a is between a first preset wind turbine surface loss level A1 and a second preset wind turbine surface loss level A2, setting a first preset repairing agent dosage B1 as a real-time repairing agent dosage, namely B = B1;
when the wind turbine surface loss level a is between a second preset wind turbine surface loss level A2 and a third preset wind turbine surface loss level A3, setting a second preset repairing agent dosage B2 as a real-time repairing agent dosage, namely B = B2;
when the wind turbine surface loss level a is between a third preset wind turbine surface loss level A3 and a fourth preset wind turbine surface loss level A4, setting a third preset repairing agent dosage B3 as a real-time repairing agent dosage, namely B = B3;
and when the wind turbine surface loss grade a is larger than a fourth preset wind turbine surface loss grade A4, setting a fourth preset repairing agent dosage B4 as a real-time repairing agent dosage, namely B = B4.
4. The method for prolonging the service life of a main speed increasing gearbox of a wind turbine generator set according to claim 3, wherein the third step comprises:
generating a restoration difference value according to the second predicted service life value of the wind turbine generator and the first preset service life value of the wind turbine generator;
and judging whether to perform compensation repair according to the repair difference value.
5. The method for prolonging the service life of the main speed increasing gearbox of the wind turbine generator set according to claim 3, wherein the judging whether to perform compensation repair according to the repair difference value comprises:
presetting a compensation coefficient matrix C, and setting C (C1, C2, C3, C4), wherein C1 is a first preset compensation coefficient, C2 is a second preset compensation coefficient, C3 is a third preset compensation coefficient, C4 is a fourth preset compensation coefficient, and C1 is more than 0 and more than C2 and more than C3 and more than C4 and less than 0.3;
presetting a restoration difference matrix D, and setting D (D1, D2, D3, D4), wherein D1 is a preset first restoration difference, D2 is a preset second restoration difference, D3 is a third preset restoration difference, D4 is a fourth preset restoration difference, and D1 is greater than D2 and less than D3 and less than D4;
acquiring a repairing difference D, and selecting a compensation coefficient c according to the relation between the real-time repairing difference D and a preset repairing difference matrix D so as to compensate and repair the wind turbine gearbox:
when the restoration difference value c is between a preset fourth restoration difference value D4 and a preset third restoration difference value D3, selecting a first preset compensation coefficient c1 to compensate the i-th preset restoration agent dosage Bi, wherein the compensation restoration agent dosage of the wind turbine gearbox is c1 Bi;
when the restoration difference value c is between a preset third restoration difference value D3 and a preset second restoration difference value D2, selecting a second preset compensation coefficient c2 to compensate the i-th preset restoration agent dosage Bi, wherein the compensation restoration agent dosage of the wind turbine generator gearbox is c2 Bi;
when the restoration difference value c is between a preset second restoration difference value D2 and a preset first restoration difference value D1, selecting a third preset compensation coefficient c3 to compensate the i-th preset restoration agent dosage Bi, wherein the compensation restoration agent dosage of the wind turbine gearbox is c3 Bi;
and when the restoration difference value c is lower than a preset first restoration difference value D1, selecting a first preset compensation coefficient c4 to compensate the ith preset restoration agent dosage Bi, wherein the compensation restoration agent dosage of the wind turbine generator gearbox is c4 Bi.
6. The utility model provides a wind turbine generator system owner increases speed gear box increase of service life's system which characterized in that includes:
the monitoring unit is used for acquiring historical operating data of a gearbox of the wind turbine generator and establishing a service life prediction model of the wind turbine generator;
the image acquisition unit is connected with the monitoring unit through a wireless signal and is used for acquiring real-time image data of the surface of a gear of the operating gear box;
and the data processing unit is connected with the monitoring unit through a wireless signal, and the image acquisition unit is used for processing the image information of the gear surface of the operating gear box acquired by the image acquisition unit and generating a repair instruction.
7. The system for extending the operational life of a wind turbine main step-up gear box according to claim 6, wherein said monitoring unit comprises:
the operation monitoring module is used for acquiring data of the accumulated operation hours, the accumulated power generation amount, the use time of the gear box and the fault operation hours of the unit and generating operation historical data;
and the image monitoring module is used for acquiring image information of the surfaces of a newly-built gear box, a fault gear box and a gear of an operated gear box of the wind turbine generator, acquiring characteristic values of surface morphology and generating historical data of the surface morphology.
8. The system for extending the operational life of a wind turbine main step-up gearbox of claim 7, wherein said monitoring unit further comprises:
and the central module is used for acquiring surface form historical data and operation historical data and establishing a wind turbine generator service life prediction model.
9. The system for extending a service life of a wind turbine main speed increasing gearbox according to claim 8, wherein said data processing unit includes:
the image information processing module is used for acquiring real-time image data of the surface of the gear of the operating gearbox and generating a characteristic value of a real-time surface form;
the first prediction module is used for acquiring a characteristic value of a real-time surface form and generating a first predicted service life value according to a life prediction model;
the first evaluation module is used for generating the surface loss grade of the wind turbine generator according to the characteristic value of the real-time surface form;
and the first repairing module is used for setting the using amount of a repairing agent according to the surface loss grade of the wind turbine generator.
10. The system for extending the operational life of a wind turbine main step-up gear box according to claim 9, wherein said data processing unit further comprises:
the second prediction module is used for acquiring the repaired surface morphology characteristic value and generating a second predicted service life value according to the service life prediction model;
the difference module generates a repair difference according to the first estimated service life value and the second estimated service life value;
and the second repairing module judges whether to perform compensation repairing according to the repairing difference value.
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