CN116428131B

CN116428131B - Wind driven generator fault early warning method and device

Info

Publication number: CN116428131B
Application number: CN202310696591.XA
Authority: CN
Inventors: 陈康; 奚瑜; 刘珊; 于佼; 刘玮; 彭怀午
Original assignee: PowerChina Northwest Engineering Corp Ltd
Current assignee: PowerChina Northwest Engineering Corp Ltd
Priority date: 2023-06-13
Filing date: 2023-06-13
Publication date: 2023-12-01
Anticipated expiration: 2043-06-13
Also published as: CN116428131A

Abstract

The disclosure provides a wind driven generator fault early warning method and device, and relates to the technical field of monitoring and early warning. The wind driven generator fault early warning method comprises the following steps: acquiring monitoring data; determining the fault level of the wind driven generator according to the monitoring data; determining corresponding fault early warning information based on the fault grade, and sending the fault early warning information to each maintenance terminal; and determining candidate maintenance terminals responding to the fault early warning information, and matching target maintenance terminals for maintaining the wind driven generator in the candidate maintenance terminals based on the fault grade. According to the wind driven generator fault early warning method, different fault early warning modes can be triggered according to different fault grades, and nearby maintenance objects can be timely informed to maintain, so that the problems that the wind driven generator is seriously damaged due to the fact that the maintenance objects do not find the wind driven generator fault for a long time are avoided, and meanwhile maintenance efficiency is improved.

Description

Wind driven generator fault early warning method and device

Technical Field

The disclosure relates to the technical field of monitoring and early warning, in particular to a wind driven generator fault early warning method, a wind driven generator fault early warning device, electronic equipment and a storage medium.

Background

This section is intended to provide a background or context to the embodiments of the disclosure recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.

With the development of society, the demand for electricity continues to rise, wind power generation is a clean energy source and short construction period is receiving widespread attention. The wind driven generator is an electric power device which converts wind energy into mechanical work and drives a rotor to rotate and finally outputs alternating current. The wind driven generator generally comprises wind wheels, a generator (comprising a device), a direction regulator (tail wing), a tower, a speed limiting safety mechanism, an energy storage device and the like. The wind wheel rotates under the action of wind force, the kinetic energy of wind can be converted into mechanical energy of a wind wheel shaft, and the generator rotates to generate electricity under the drive of the wind wheel shaft.

At present, in the related wind driven generator fault early warning and maintenance scheme, detection maintenance is required to be carried out regularly in order to ensure the normal operation of a fan, but maintenance personnel are required to go to the vicinity of a destination to carry out manual fault early warning and investigation on the wind driven generator, so that the fault discovery time is relatively late, and the detection maintenance efficiency is relatively low; in addition, when a plurality of wind driven generators send out early warning simultaneously, the wind driven generator with serious faults cannot be detected rapidly and is repaired preferentially, so that the damage fault rate of the wind driven generator is higher.

Disclosure of Invention

In order to overcome the problems in the related art, the present disclosure provides a wind turbine fault early warning method, a wind turbine fault early warning device, an electronic device, and a storage medium.

According to a first aspect of an embodiment of the present disclosure, there is provided a wind turbine fault early warning method, the method including:

acquiring monitoring data;

determining the fault level of the wind driven generator according to the monitoring data;

determining corresponding fault early warning information based on the fault grade, and sending the fault early warning information to each maintenance terminal;

and determining candidate maintenance terminals responding to the fault early warning information, and matching target maintenance terminals for maintaining the wind driven generator in the candidate maintenance terminals based on the fault grade.

According to a second aspect of the embodiments of the present disclosure, there is provided a wind turbine fault early warning device, including:

the data acquisition module is used for acquiring monitoring data;

the state judging module is used for determining the fault level of the wind driven generator according to the monitoring data;

the fault early warning module is used for determining corresponding fault early warning information based on the fault grade and sending the fault early warning information to each maintenance terminal;

And the maintenance object matching module is used for determining candidate maintenance terminals responding to the fault early warning information and matching target maintenance terminals for maintaining the wind driven generator in the candidate maintenance terminals based on the fault grade.

According to a third aspect of embodiments of the present disclosure, there is provided an electronic device comprising: a processor, a memory, and a program stored on the memory and executable on the processor;

and when the program is executed by the processor, any step of the wind driven generator fault early warning method is realized.

According to a fourth aspect of embodiments of the present disclosure, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements any step of the wind turbine fault warning method.

The technical scheme provided by the embodiment of the disclosure can comprise the following beneficial effects:

according to the embodiment of the disclosure, the monitoring data of the wind driven generator can be obtained, then the fault grade of the wind driven generator can be determined according to the monitoring data, different fault early warning modes are triggered based on the fault grade, and the corresponding maintenance terminals are matched, so that maintenance objects corresponding to the maintenance terminals maintain the wind driven generator. On one hand, the wind driven generator is monitored in real time to obtain monitoring data, and then the fault grade of the wind driven generator can be rapidly determined according to the monitoring data, so that a corresponding fault early warning mode is rapidly executed according to the fault grade, a maintenance object can discover that the wind driven generator breaks down at first time, then the wind driven generator is maintained according to the fault grade, and the problems that the wind driven generator is discovered to be later in time and low in maintenance efficiency due to the fact that the wind driven generator is subjected to fault early warning and investigation one by one after the maintenance object arrives at the site in a related scheme are avoided, and therefore the detection and maintenance efficiency of the wind driven generator is improved; on the other hand, different fault early warning modes are adopted for different fault grades, so that a maintenance object can judge the fault grade of the fault wind driven generator at the first time when the fault early warning information is received, the interpretation time of the maintenance object on the fault information of the target wind driven generator is shortened, the maintenance flow is shortened, and the maintenance efficiency is accelerated; on the other hand, the corresponding fault early warning is sent out based on the fault level, so that a proper maintenance terminal is matched, maintenance of the wind driven generator at the current fault level can be guaranteed to be completed by a maintenance object corresponding to the maintenance terminal, the problem that the wind driven generator cannot be timely maintained due to replacement of the maintenance object is avoided, the maintenance efficiency of the wind driven generator is improved, the wind driven generator with a higher fault level is timely maintained, and the damage fault rate of the wind driven generator is further reduced.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.

FIG. 1 is a flowchart of a wind turbine fault pre-warning method according to an exemplary embodiment of the present disclosure.

Fig. 2 is an application scenario diagram of a wind turbine fault early warning method according to an exemplary embodiment of the present disclosure.

FIG. 3 is a flowchart illustrating a method of determining a failure level according to an exemplary embodiment of the present disclosure.

FIG. 4 is an exemplary flow chart illustrating determining different fault early warning modes based on fault level determination values according to an exemplary embodiment of the present disclosure.

FIG. 5 is a block diagram of a wind turbine fault early warning device according to an exemplary embodiment of the present disclosure.

Fig. 6 is a block diagram of a maintenance terminal according to an exemplary embodiment of the present disclosure.

Fig. 7 is a line graph illustrating one type of time-lapse data visualization result according to an exemplary embodiment of the present disclosure.

Fig. 8 is a hardware configuration diagram of a computer device where the wind turbine fault early warning device according to the embodiment of the disclosure is located.

FIG. 9 is a wind turbine and service terminal position reference diagram illustrating a specific example of an embodiment of the present disclosure.

Detailed Description

Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present disclosure as detailed in the accompanying claims.

The terminology used in the present disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used in this disclosure and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any or all possible combinations of one or more of the associated listed items.

It should be understood that although the terms first, second, third, etc. may be used in this disclosure to describe various information, these information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present disclosure. The word "if" as used herein may be interpreted as "at … …" or "at … …" or "responsive to a determination", depending on the context.

Embodiments of the present disclosure may be implemented as a system, apparatus, device, method, or computer program product. Accordingly, the present disclosure may be embodied in the following forms, namely: complete hardware, complete software (including firmware, resident software, micro-code, etc.), or a combination of hardware and software. Meanwhile, the present disclosure does not limit the type of the operating system of the electronic device. For example, android systems, linux systems, windows systems, IOS systems, etc.

In this context, it is to be understood that, in the terms referred to:

a terminal (english terminal) is an input/output device connected to a computer system, and is usually located far from the computer. According to the function, the functions can be divided into a plurality of classes. Terminals with certain processing functions are called smart terminals or intelligent terminals, which have their own microprocessors and control circuits; a so-called dumb terminal without this function, which has no microprocessor. Terminals supporting sessions or processes with computers are called interactive terminals or online terminals. Common in daily life are: cell phones, notebooks, tablets, POS devices even include car computers, and desktop computers.

With the increasing energy demand, wind power generation is used as a clean energy source and the construction speed is high. In the running process of the wind driven generator, larger or smaller faults sometimes occur to cause damage to components, if the components cannot be repaired in time, the power generation efficiency is greatly reduced, even a series of other components can be damaged due to long-term damage of part of the components, and the fault finding time and the maintenance speed are particularly important.

In the related art, there are the following problems:

when wind power generation is performed, regular detection and maintenance are required to ensure the normal operation of the wind power generator, but due to different distances between a maintenance object and each wind power generator, the maintenance object needs a long time to patrol the wind power generator with a longer distance. If a remote wind driven generator fails and gives an early warning, but the maintenance object is hindered to take a long time to patrol, the failure degree of the wind driven generator, the damage degree of parts and the maintenance difficulty of the maintenance object may be increased in the process.

When a wind driven generator fails, various factors (temperature, ambient wind power, blade state, rotating speed and the like) are often included, the related wind driven generator monitoring scheme can simply judge the data type only through collected monitoring data, and the specific maintenance sequence is difficult to determine by accurately sequencing the failure degree of the wind driven generator.

In the related wind power generator monitoring scheme, the wind power generator can only determine whether the wind power generator is in a fault state, and in the application scene of the method, a maintenance object is always in a passive side, and maintenance can be performed only after the fault occurs. When a plurality of wind power generators simultaneously fail, there may be a problem that the maintenance object is not configured enough.

Based on one or more problems in the related art, the embodiments of the present disclosure first provide a wind turbine fault early warning method, which may be executed by a terminal device or a server, and a server execution method is described below as an example.

As shown in fig. 1, fig. 1 is a flowchart of a wind turbine fault early warning method according to an exemplary embodiment of the present disclosure, including the steps of:

in step S101, monitoring data is acquired;

step S102, determining the fault level of the wind driven generator according to the monitoring data;

step S103, corresponding fault early warning information is determined based on the fault level, and the fault early warning information is sent to each maintenance terminal;

in step S104, candidate maintenance terminals responding to the fault early warning information are determined, and target maintenance terminals for maintaining the wind turbine are matched in the candidate maintenance terminals based on the fault level.

According to the wind driven generator fault early warning method, monitoring data of the wind driven generator can be obtained, then fault grades of the wind driven generator can be determined according to the monitoring data, different fault early warning modes are triggered based on the fault grades, and corresponding maintenance terminals are matched, so that maintenance objects corresponding to the maintenance terminals maintain the wind driven generator. On one hand, the fault grade of the wind driven generator is monitored in real time, so that different fault early warning modes are triggered according to the fault grade, corresponding maintenance terminals are matched, a maintenance object is timely informed of maintaining the wind driven generator according to the fault grade shown by the fault early warning mode, the problem that the damage fault rate of the wind driven generator is high due to the fact that the wind driven generator with higher fault grade cannot be timely maintained can be effectively avoided, the damage fault rate of the wind driven generator is reduced, and maintenance cost is reduced; on the other hand, the maintenance efficiency of the wind driven generator can be effectively improved based on the matching of the fault level and the proper maintenance terminal, so that the wind driven generator with higher fault level is timely maintained, and the damage fault rate of the wind driven generator is further reduced.

Next, steps S101 to S104 will be described in detail.

In step S101, monitoring data is acquired.

In an exemplary embodiment of the present disclosure, the monitoring data refers to data related to the function of the wind power generator, which is monitored from the wind power generator by related monitoring means, for example, the monitoring data may be temperature change data collected by a temperature sensor provided on the wind power generator; the monitoring data may also be current change data obtained by monitoring current data output by the wind driven generator through the current detection device, and of course, the monitoring data may also be a working state, a rotor rotation speed, an ambient wind force, a blade vibration frequency, a blade inclination angle degree and the like corresponding to the wind driven generator, and the data type of the present exemplary embodiment for representing the function of the wind driven generator is not particularly limited.

The monitoring data of the wind driven generator can be obtained from each monitoring device through the data acquisition interface, the monitoring data of the wind driven generator can also be obtained from the operation log of the wind driven generator, and the monitoring data of the wind driven generator can be obtained by the input of a monitoring person through the provided data window, so that the obtaining mode of the monitoring data is not limited.

In step S102, a fault level of the wind turbine is determined according to the monitoring data.

In an exemplary embodiment of the present disclosure, the fault level refers to dividing the fault level into several levels according to the degree of the fault level of the wind turbine, for example, the fault level may be divided into one level, two levels, three levels, four levels, five levels, where one level represents the lowest fault level, and five levels represent the highest fault level, and may also be divided into level a, level B, level C, level D, level E, where the level a has the lowest fault level, and level E has the highest fault level, and of course, may also be divided into a negligible level, a low level, a normal level, a high level, an urgent level, and the negligible level has the lowest fault level, and the urgent level has the highest fault level.

The failure level of the wind turbine may be determined according to the number of data types of the failed monitoring data, or, of course, the failure level of the wind turbine may be determined according to the weight of the data types of the failed monitoring data, and the division basis of the failure level in the present exemplary embodiment are not particularly limited.

In step S103, corresponding fault early warning information is determined based on the fault level, and the fault early warning information is sent to each maintenance terminal.

In an example embodiment of the present disclosure, the fault early warning information refers to an information notification that quickly alerts the maintenance object to find a fault before or when the fault occurs in various ways. For example, the failure warning information may be information acting on hearing, may be information acting on vision, or may be information acting on touch. The present exemplary embodiment does not particularly limit the form of the failure warning information.

The maintenance object can be reminded through the prompt bell of the maintenance terminal, and also can be reminded through the signal display lamp of the maintenance terminal, and of course, the maintenance object can also be reminded through the vibration of the maintenance terminal. The present exemplary embodiment does not particularly limit the transmission manner of the failure warning information.

By making different early warning modes for different fault grades, a maintenance object can judge the fault grade of the fault wind driven generator at the first time of receiving the fault early warning information, thereby shortening the maintenance flow of the wind driven generator and accelerating the maintenance efficiency.

In an example embodiment of the present disclosure, the maintenance terminal refers to an electronic device dedicated for maintenance, where a maintenance object is used to receive wind turbine failure early warning information transmitted from a server and send information to the server. For example, the maintenance terminal may be a mobile phone which is convenient for a maintenance person to carry, or may be a desktop computer with better performance, or may be a notebook, a tablet computer, a vehicle-mounted computer, or the like, and the specific form of the maintenance terminal is not particularly limited in this example embodiment.

Wherein, the maintenance object refers to an execution main body for solving the problem of wind driven generator faults. For example, the maintenance target may be a maintenance person, or may be an intelligent machine or the like capable of completing maintenance of the wind turbine, and the present exemplary embodiment is not particularly limited in terms of the type of maintenance target.

The repair object closest to the wind turbine may be matched according to the failure level, or the repair tool may be matched according to the failure level to configure the most complete repair object, or of course, the repair object with the highest performance of the corresponding failure type may be matched according to the failure level, and the selection manner of the candidate repair object is not particularly limited in this exemplary embodiment.

The wind driven generator is monitored in real time, the fault grade of the wind driven generator is rapidly determined, so that a maintenance terminal is matched according to the fault grade, and early warning is timely sent out to enable a maintenance object to maintain the wind driven generator according to the fault grade, so that the problem that the wind driven generator with higher fault grade cannot be timely maintained, and the damage fault rate of the wind driven generator is higher is effectively avoided, and the maintenance cost is reduced; on the other hand, the maintenance efficiency of the wind driven generator can be effectively improved based on the matching of the fault level and the proper maintenance terminal, so that the wind driven generator with higher fault level is timely maintained, and the damage fault rate of the wind driven generator is further reduced.

The technical solutions involved in step S101 to step S104 are explained in detail below.

In an example embodiment of the present disclosure, step S103 may be implemented by:

and determining a fault early-warning mode based on the fault grade, and generating fault early-warning information corresponding to the fault grade according to the determined fault early-warning mode.

The fault early warning mode is the most suitable transmission early warning mode selected according to the content of the fault early warning information. For example, the fault early warning mode may adopt a buzzer early warning mode, a display lamp early warning mode, or an early warning mode of fault information pushing, and of course, fault early warning may also be performed by adopting one or more of a buzzer, a display lamp and fault information pushing.

Optionally, for the wind driven generator at each level, different fault early warning modes are adopted to quickly inform the maintenance object, so that the maintenance process is quickened. The following describes the fault early warning mode adopted by each fault level in detail:

the first fault level adopts a buzzer early warning mode;

the second fault level adopts a display lamp early warning mode;

the third fault level adopts a corresponding fault information pushing and early warning mode;

a fourth fault level adopts at least two of buzzer early warning, display lamp early warning and fault information pushing early warning modes;

and fifth fault level adopts a corresponding buzzer early warning, display lamp early warning and fault information pushing early warning mode.

Specifically, for the second fault level, the fourth fault level, and the fifth fault level, since the display lamp early warning mode is adopted or included in the fault early warning modes, for distinguishing different fault levels, the display lamp can adopt the following scheme:

the display lamp is green, and the wind driven generator is at a first fault level or has no fault;

the display lamp is blue, and the wind driven generator is indicated to be at a second fault level;

the display lamp is white, and the wind driven generator is indicated to be at a third fault level;

The display lamp is yellow, which indicates that the wind driven generator is at a fourth fault level;

the display lamp is red, which indicates that the wind driven generator is at the fifth fault level.

Different colors are displayed on different fault levels through the display lamp, and a maintenance object can quickly identify the fault level of the corresponding wind driven generator through the color prompt of the display lamp, so that the work flow of the maintenance object is shortened.

The fault level of the current wind driven generator is judged by the maintenance object according to the different early warning modes or the different display lamp colors, so that the monitoring maintenance efficiency is improved, and the time for the maintenance process is shortened.

In an example embodiment of the present disclosure, the determination of the failure level of the wind turbine in step S102 may be achieved by:

when detecting that fault data exists in the monitoring data, the number of data types corresponding to the monitoring data with the fault data is determined, and then the fault grade of the wind driven generator can be determined according to the number of data types.

The fault data refers to record data for expressing main characteristics of fault event (such as fault mode, type, cause, location, influence and result, occurrence time and the like). For example, the fault data may be an accurate value, or may be a cause of a fault, or may be a fault mode, a fault type, a fault location, a fault influence, a fault result, a time of occurrence of a fault, or the like. The present exemplary embodiment does not particularly limit the specific type of the fault data.

Different fault levels can be formulated according to the number of each data type, the number of the data types can be divided, and then different fault levels can be formulated for each division interval. The basis of the division of the failure level according to the present exemplary embodiment is not particularly limited.

For example, if a wind turbine fails, the server may obtain all types of failure data, including: component temperature data, ambient wind data, rotor speed data, blade status data, power generation data, and the like. The fault data types may be divided for each of the above five data types, such as the following division: when the fault data type is only one item, the fault level is set as one level; when the fault data type has any two of the above items, the fault grade is determined as a second grade; when the fault data type has any three items, the fault level is determined to be three-level; when the fault data type has any four items, the fault level is determined to be four levels; when the fault data type has all the five items, the fault level is set to five. Of course, the following division may also be employed: when the fault data type is only one item, the fault level is set as one level; when the fault data type has any two or three items, the fault grade is determined as a second grade; when the fault data type has any four or five items, the fault level is set to be three.

By the wind driven generator fault early warning method, the fault grade of the wind driven generator can be rapidly determined by simply judging the type number of the fault data, so that fault early warning is rapidly sent out, the maintenance flow of maintenance objects is facilitated, and the time required for maintenance is reduced.

In an exemplary embodiment of the present disclosure, the determination of the failure level of the wind turbine in step S102 may also be implemented through the steps in fig. 3, and is shown with reference to fig. 3:

step S301, acquiring weight data set for each data type of the monitoring data;

step S302, in response to detecting that fault data exists in the monitoring data, determining a fault grade influence value corresponding to the monitoring data with the fault data according to the weight data;

and step S303, determining the fault grade of the wind driven generator according to the fault grade influence value.

The weight data of a certain index refers to the relative importance of the index in the overall evaluation. The weight data may be changed, for example, the weight data of some two indexes A, B may be 1 and 2, and then the importance of a is 1/3 and the importance of b is 2/3. Of course, it is also possible to set 3 and 7, and the importance of A is 3/10 and the importance of B is 7/10. The present exemplary embodiment does not particularly limit the setting of the weight data.

The weight data may be obtained through a weight mapping table, or may be obtained through an association relationship or a database. The present exemplary embodiment does not particularly limit the manner of acquiring the weight data.

The fault level influence value is that firstly, calculating the change amplitude value of the data, then multiplying the change amplitude value with the weight data to obtain the fault level influence value of the data type, and when the data type of the fault data is more than one, adding the fault level influence values corresponding to the data to obtain a final value.

As to how to determine the corresponding failure level influence value from the plurality of weight data, there are the following examples:

assuming that the types of monitoring data of the wind driven generator include component temperature, ambient wind force and rotor speed, it can be assumed that the three data have different degrees of influence on the fault level. Assuming that the weight of the component temperature data is 5, the weight of the ambient wind force is 1, and the weight of the rotor speed is 4.

In addition, the temperature standard value of a certain component of the wind driven generator in a certain region is assumed to be 40 ℃, the ambient wind power standard value is 25m/s, and the rotor rotating speed standard value is 3000 revolutions per minute. The current four wind power generators are set as A, B, C, D in sequence, and the real-time monitoring data of the four wind power generators about three data types are assumed to be:

Wind power generator A: the temperature data of the parts is 65 ℃, the ambient wind power data is 30m/s, and the rotor rotating speed data is 2700 revolutions per minute;

wind power generator B: the temperature data of the parts is 45 ℃, the ambient wind power data is 10m/s, and the rotor rotating speed data is 2000 revolutions per minute;

wind power generator C: the temperature data of the parts is 80 ℃, the ambient wind power data is 40m/s, and the rotor rotating speed data is 4800 revolutions per minute;

wind power generator D: the temperature data of the parts is 50 ℃, the ambient wind power data is 35m/s, and the rotating speed data of the rotor is 3000 rpm.

Then the failure level influence value of the wind driven generator a can be calculated as (65-40) ×0.5/40+ (30-25) ×0.1/25+ (3000-2700) ×0.4/3000=0.3725 according to the foregoing calculation method; the failure rank influence value of the wind power generator B is (45-40) ×0.5/40+ (25-10) ×0.1/25+ (3000-2000) ×0.4/3000= 0.2559; the failure level influence value of the wind power generator C is (80-40) multiplied by 0.5/40+ (40-25) multiplied by 0.1/25+ (4800-3000) multiplied by 0.4/3000=0.8; the failure level influence value of the wind power generator D is (50-40) ×0.5/40+ (35-25) ×0.1/25+ (3000-3000) ×0.4/3000=0.165.

For determining the fault level of the wind driven generator according to the fault level influence value, the fault level influence value may be classified into a fault level with 0.1 as a section, or may be classified into a fault level with 0.2 as a section, or other classification manners. The present exemplary embodiment does not particularly limit the manner of dividing the failure level influence value. The failure classification of the wind driven generator obtained by the previous step example is as follows:

The fault level can be divided into 5 levels, namely a first level, a second level, a third level, a fourth level and a fifth level, and the fault level gradually deepens along with the rise of the level. Assuming that the fault level influence value is more than or equal to 0.1 and less than 0.2, the fault level of the wind driven generator is one level; when the fault level influence value is more than or equal to 0.2 and less than 0.3, the fault level of the wind driven generator is two-level; when the fault level influence value is more than or equal to 0.3 and less than 0.4, the fault level of the wind driven generator is three-level; when the fault level influence value is more than or equal to 0.4 and less than 0.5, the fault level of the wind driven generator is four; when the fault level influence value is more than or equal to 0.5, the fault level of the wind driven generator is five. The failure level of the wind power generator A, B, C, D in the above example is three, two, five, and one in order according to the above failure level classification standard.

Alternatively, when the failure level influence value of the wind power generator is less than 0.1, the wind power generator may be determined as a no-failure or low-failure wind power generator.

Alternatively, in addition to the standard value, a small-range value wobble interval may be set for the values of the respective data types based on the standard value, i.e., the values in the wobble interval are all regarded as normal data. For example, if the standard value of the component temperature data is 40 ℃, and the swing interval is [38 ℃,42 ℃), the data in the interval is regarded as normal data, and the calculation of the fault level influence value is not included.

Optionally, a threshold value may also be set for the value of each data type. When the data exceeds the critical value, the server 100 directly ranks the target wind turbine into the fifth failure level without calculating the failure level influence value. For example, the above-mentioned critical values of the rotor speed may be set to 1000 rpm and 5000 rpm, assuming that the target wind turbine is directly rated into the fifth failure level when a speed of 500 rpm, i.e. less than 1000 rpm, or 6000 rpm, i.e. greater than 5000 rpm, is detected.

According to the wind driven generator fault early warning method, the influence degree of the large value and the small value on the fault grade is balanced by using the weight data, and the judgment of the fault grade is more accurate through accurate calculation steps, so that the wind driven generator with high fault grade is more quickly maintained.

In an example embodiment of the present disclosure, the wind power generator fault early warning method of the wind power generator based on the fault level matching maintenance terminal in step S103 may also be implemented by the following steps:

the wind driven generators can be sequenced according to the fault level, the maintenance priority of each wind driven generator is determined, and then the maintenance terminal is matched according to the maintenance priority.

The maintenance priority refers to that in the maintenance process, the first with high maintenance priority is maintained, and the second with low maintenance priority is maintained. The priorities may be a first priority, a second priority, a third priority, a fourth priority, a highest priority, a high priority, a medium priority, a low priority, or an urgent and important, important but not urgent, urgent but not important, not urgent but not important. The present exemplary embodiment does not particularly limit the manner of dividing the maintenance priority.

The wind driven generators are ranked according to the fault level, and can be ranked from low to high or from high to low. The present example does not particularly limit the manner of ordering the wind power generators.

For example, A, B, C, D, E five wind generators, the failure grades of which are one, three, four and five, respectively, may have the maintenance priorities ordered as E > D > b=c > a. In the process of matching the maintenance terminal subsequently, the maintenance terminal is matched with E, then D, any one of B and C, the other one of B and C, and finally A with the lowest maintenance priority.

The present exemplary embodiment proposes to sort the maintenance priorities of the wind power generators, and aims to make all the wind power generators maintain successively according to the fault degree, thereby reducing the fault damage rate of the wind power generators.

In an example embodiment of the present disclosure, ranking wind turbines by failure level to determine maintenance priority of the wind turbines may be accomplished by the steps shown in FIG. 4:

the fault grade determination value can be obtained, then the wind driven generator with the fault grade greater than or equal to the fault grade determination value is determined as the target wind driven generator, and then the target wind driven generators are sequenced according to the fault grade of the target wind driven generator, so that the maintenance priority of each target wind driven generator is determined.

The failure level determination value refers to a value preset in advance for determining the failure level, i.e., dividing the failure level into target wind power generators and remaining wind power generators according to the failure level of the wind power generator. The failure level determination value is not limited to the form, and may be any form exemplified by the above failure level classification method, for example, three, important, but not urgent, medium, or any numerical value thereof, for example, one, two, three, and four. The present exemplary embodiment does not particularly limit the form and the numerical value of the failure level determination value. The manner of acquiring the failure level is the same as the manner of acquiring the weight data described above, and the manner of acquiring the failure level is not particularly limited.

For example, assuming that the failure level determination value is "three" for the aforementioned wind turbine A, B, C, D, E, then B for the failure level three, C for the failure level three, D for the failure level four, and E for the failure level five are determined as target wind turbines, then the failure levels of B, C, D, E are ordered to obtain E > D > b=c, and the highest priority is obtained, E, then D, then either B or C, and finally the other one of B or C. And then the maintenance of the target wind driven generator is only required according to the maintenance priority.

By sorting the fault grades of the wind driven generators, excluding the wind driven generators with lower fault grades, and sorting the wind driven generators with higher fault grades, the difficulty and the flow of the fault grade sorting can be reduced, and the time for the sorting step is shortened, so that the maintenance speed of the target wind driven generator is increased.

In an example embodiment of the present disclosure, the step of matching the maintenance terminal based on the failure level may be accomplished by the steps shown in fig. 4:

the wind driven generator with the highest priority can be determined according to the maintenance priority, positioning information of each maintenance terminal is obtained, then the maintenance terminal closest to the wind driven generator with the highest priority is matched according to the positioning information and the position coordinates of the wind driven generator with the highest priority, and a maintenance notification is sent to a maintenance object.

The maintenance notification refers to information issued to the maintenance object through the maintenance terminal after the server acquires the information of the target wind turbine, and the maintenance notification can be positioning information of the target wind turbine, positioning information of the target wind turbine and a fault cause. For example, "40°n,116°e, the failure level is three stages, the hydraulic pump temperature, and the temperature is too low. The present exemplary embodiment does not particularly limit the content of the maintenance notification.

The method for obtaining the positioning information of each maintenance terminal may be to obtain preset information, that is, the same as the method for obtaining the weight data and the fault level determination value in the foregoing embodiment, or may be to obtain the GPS positioning information of the maintenance terminal in real time, or may, of course, send information to the maintenance terminal, so that the maintenance object fills in the positioning information of the maintenance terminal by itself. The present exemplary embodiment does not particularly limit the manner of acquiring the maintenance terminal.

Optionally, if the duration of the service object which is closest to the server is not recovered exceeds a certain value, the server informs the next service object which is closest to the server, and pushes down the next service object in turn. For example, from the above example, the maintenance priority ranking is E > D > b=c, and the wind power generator E with the highest maintenance priority may be the wind power generator with the highest priority. Assuming that there are maintenance terminals M, N, S, T at distances 1km, 2.5km, 1.5km, 5km from wind turbine E, the distances between each maintenance terminal and E are ordered by 1 < 1.5 < 2.5 < 5, then M is considered as the closest maintenance terminal to wind turbine E, and the server then sends a maintenance notification about wind turbine E to M. If the maintenance object matched with M does not pass through the maintenance terminal M to recover the server for a long time, the server can send a maintenance notification to the maintenance terminal S with the distance of 1.5km, and the maintenance terminals S are pushed down in sequence.

Optionally, after determining the wind driven generator with the highest priority, the server acquires the position information of the rest target wind driven generators and compares the position information with the working area of the maintenance object matched with the wind driven generator with the highest priority so as to check whether the maintenance object is located in the working area of the maintenance object. When the target wind driven generator is in the working area, maintaining the wind driven generator with the highest priority, and then maintaining the other target wind driven generators; when the target wind power generator is out of the working area, the target wind power generator is matched with the maintenance object closest to the target wind power generator.

The present exemplary embodiment matches the most-recently serviced terminal for the most-recently serviced wind turbine, and may match the next most-recently serviced terminal when the most-recently serviced terminal has no feedback, which is to place the most-recently serviced wind turbine's service in the first place to avoid greater damage to the most-recently serviced wind turbine.

In an example embodiment of the present disclosure, preventative maintenance of a wind turbine may be accomplished by the steps shown in FIG. 4:

the performance state of the wind driven generator with the fault level smaller than the fault level judgment value can be determined according to the monitoring data, and preventive maintenance is carried out on the wind driven generator based on the performance state.

The performance state refers to the performance or state change of the wind driven generator after the deviation of the monitoring data of the wind driven generator. For example, the performance state is overheated when the component temperature data is higher, aging when the rotor speed data is lower, and the like. The present exemplary embodiment does not particularly limit the performance state content of the wind turbine.

The preventive maintenance means that when the monitoring data of the wind driven generator is deviated but the failure of the wind driven generator is not caused, a maintenance object needs to maintain the monitoring data of the wind driven generator in advance before the failure occurs, so that the monitoring data of the wind driven generator returns to the normal range, and the occurrence probability of the subsequent failure is reduced. The present exemplary embodiment does not particularly limit the pre-time range of preventive maintenance.

Optionally, the monitoring data with offset monitoring data is set on top, and the abnormal data is highlighted on a maintenance terminal display page, so that a maintenance object is quickly helped to know the data type with data offset, and the wind driven generator is correspondingly and effectively maintained in a preventive manner.

For example, assuming that the standard rotor speed of the wind turbine is 3000 rpm, the yaw zone is [2900 rpm, 3100 rpm ], and the rotor speed of the wind turbine O having a certain failure level smaller than the failure level determination value is 2800 rpm, it is determined that the performance state of the wind turbine O is aged at this time, the rotor speed data in which the deviation occurs is highlighted on the maintenance terminal, the aged two words are displayed in the vicinity of the rotor speed data, and then the maintenance subject makes an optimal preventive maintenance measure according to the performance state.

In the wind power generator fault early warning method, the wind power generator with offset monitoring data is maintained in advance through preventive maintenance, and the wind power generator is prevented in advance when faults do not occur, so that the fault occurrence rate of the subsequent wind power generator is reduced, and the subsequent maintenance difficulty of a maintenance object is reduced.

In an example embodiment of the present disclosure, the type of the repair tool required for the repair of the fault may also be determined according to the fault data occurring in the monitoring data, and then the fault grade and the type of the repair tool may be transmitted to the target repair terminal based on the fault grade and the type of the repair tool matching the target repair terminal.

The maintenance tool can be a motor dismounting tool, a winding tool, a detection tool and the like. The number and content of the types of the maintenance tools are not particularly limited in this example.

In the wind driven generator fault early warning method, by analyzing fault data, the subsequent possible maintenance tools are prompted, the phenomena of fewer maintenance objects and wrong maintenance tools are avoided, and the maintenance efficiency and the maintenance success rate of the maintenance objects are improved.

Fig. 2 is a diagram illustrating an application scenario of a wind turbine fault early warning method according to an exemplary embodiment of the disclosure. The scenario shown in fig. 2 includes a server 100, a monitoring device 200, and a maintenance terminal 300. The server 100 may be a software operator server or the like. The monitoring device 200 may include vibration sensors, dynamic strain gauges, dynamic inclinometers, cable sensors, hydrostatic levels, hygrothermographs, and the like. By means of the equipment, component temperature data, environment wind power data, blade state data, rotor rotating speed data and the like of the wind driven generator are mainly obtained, wherein the blade state data can be blade vibration data or blade inclination angle data. The maintenance terminal 300 may be a mobile terminal, such as a mobile electronic device including a mobile phone, a tablet computer, a notebook computer, a personal digital assistant, or a desktop computer. The server 100 and the monitoring device 200 may be electrically connected. The server 100 and the maintenance terminal 300 may be connected to each other via the mobile internet or the like.

When a maintenance object needs to view monitoring data of a wind turbine, the monitoring data of the wind turbine may be presented in real time or in time periods on the maintenance terminal 300, more specifically, for example, on a software interface installed on the maintenance terminal 300, and more specifically, may be presented in various data visualization manners.

Alternatively, the processing of the monitoring data may be performed on the server 100 or on the maintenance terminal 300, and the user may download the application software through the server 100, and the application software may embed a program of steps such as data processing. That is, the steps in the method of the embodiment of the present disclosure to be described next may be performed entirely by the server side, or may be performed entirely by the maintenance terminal side, or may be performed partly by the server side, or partly by the maintenance terminal.

Next, a wind power generator failure warning apparatus according to an exemplary embodiment of the present disclosure will be described with reference to fig. 5.

As shown in fig. 5, the wind power generator failure early warning apparatus may include: a data acquisition module 5101, a failure level discrimination module 5102, a failure early warning module 5103, and a maintenance object matching module 5104.

The data acquisition module 5101 is configured to acquire monitoring data.

The fault level discrimination module 5102 is configured to determine a fault level of the wind turbine according to the monitoring data.

The fault early-warning module 5103 is configured to determine corresponding fault early-warning information based on the fault level, and send the fault early-warning information to each maintenance terminal.

Repair object matching module 5104 is configured to determine candidate repair terminals for responding to the fault warning information, and match target repair terminals for repairing the wind turbine among the candidate repair terminals based on the fault level.

In an example embodiment of the present disclosure, the fault early warning module 5103 is configured to:

determining a fault early warning mode based on the fault grade, wherein the fault early warning mode comprises any one or a combination of a plurality of buzzer early warning, display lamp early warning and fault information pushing early warning;

generating fault early warning information corresponding to the fault grade according to the determined fault early warning mode.

In an example embodiment of the present disclosure, the failure level discrimination module 5102 is set to:

in response to detecting that fault data exists in the monitoring data, determining the number of data types corresponding to the monitoring data with the fault data;

and determining the fault level of the wind driven generator according to the data type quantity.

acquiring weight data set for each data type of the monitoring data;

in response to detecting that fault data exists in the monitoring data, determining a fault grade influence value corresponding to the monitoring data with the fault data according to the weight data;

And determining the fault grade of the wind driven generator according to the fault grade influence value.

In an example embodiment of the present disclosure, the repair object matching module 5104 is set to:

sequencing the wind driven generators according to the fault level, and determining the maintenance priority of each wind driven generator;

and matching the maintenance terminal according to the maintenance priority.

obtaining a fault grade judgment value;

determining the wind driven generator with the fault level being greater than or equal to the fault level determination value as a target wind driven generator;

and sequencing the target wind power generators according to the fault level of the target wind power generator, and determining the maintenance priority of each target wind power generator.

determining the wind driven generator belonging to the highest priority according to the maintenance priority;

acquiring positioning information of each maintenance terminal;

and matching the position information and the position coordinates of the wind driven generator belonging to the highest priority to a maintenance terminal closest to the wind driven generator belonging to the highest priority, and sending a maintenance notification to the maintenance object.

determining the performance state of the wind driven generator with the fault level smaller than the fault level judgment value according to the monitoring data;

and performing preventive maintenance on the wind driven generator based on the performance state.

determining the type of a maintenance tool required by fault maintenance according to fault data in the monitoring data;

and based on the fault grade and the maintenance tool type, matching a target maintenance terminal, and sending the fault grade and the maintenance tool type to the target maintenance terminal.

The device comprises a data acquisition module 5101, a fault level judging module 5102, a fault early warning module 5103 and a maintenance object matching module 5104, wherein the data acquisition module, the fault level judging module, the fault early warning module 5103 and the maintenance object matching module 5104 can be arranged at a mobile terminal or a PC end, and a user can finish similar operation at the PC end, so that the device is a universal wind driven generator fault early warning device.

Corresponding to the embodiments of the aforementioned method, the present disclosure also provides embodiments of the apparatus and the terminal to which it is applied.

Fig. 6 is a block diagram of a maintenance terminal 300 according to an exemplary embodiment of the present disclosure.

As illustrated in fig. 6, the maintenance terminal 300 may include: a data receiving module 6101, a data storage module 6102, a data processing module 6103, a tool analysis module 6104, a data visualization display module 6105. The data receiving module 6101 may further include a data input module and a data transmitting module.

The data receiving module 6101 is configured to receive fault information from the server 100 and other information such as target wind turbine position information, and may be used for data transmission with the server 100 or other maintenance terminals 300.

The data storage module 6102 is configured to store the received data from the server 100, generate a log according to the corresponding date and operation adjustment, and store the log, so as to facilitate checking during subsequent inspection or maintenance to understand the recent working condition of the corresponding wind turbine.

A data processing module 6103 for processing the data stored in the data storage module 6102.

The tool analysis module 6104 is configured to analyze a tool type required for repairing the fault according to the processed data, so as to avoid a situation that the repairing object has fewer tools.

The data visualization display module 6105 is configured to change the processed data into a form more convenient for the maintenance object to interpret by a technical means of data visualization.

Optionally, the data receiving module 6101 may include a data input module and a data transmitting module. The maintenance object may edit the data that it wants to modify or input information that it wants to send to other maintenance devices through the data input module. The modifiable data may include, among other things, component temperature data, rotational speed data, ambient wind data, blade status data, and the like.

Optionally, after the maintenance terminal has successfully maintained the failed wind turbine, the maintenance object may send a request to the server 100 through the data sending module to recalculate the failure level impact value of the target wind turbine, thereby completing the modification of the failure state of the target wind turbine.

Alternatively, the maintenance object may also send a request for replacement of the maintenance object to the server 100 through the data transmission module. Similarly, after the data receiving module 6101 receives the maintenance notification issued by the server 100, if the maintenance object does not send the confirmation information to the server 100 through the data sending module within a predetermined time, the data sending module will send a request to replace the maintenance object to the server 100 by itself.

Similarly, the maintenance terminal 300 is further provided with a data storage module 6102, which is mainly used for storing the data received by the data receiving module 6101, the data processed by the data processing module 6103, and the data modified by the maintenance object through the data receiving module 6101. Wherein the data storage module 6102 is configured to employ at least one of a semiconductor memory, a magnetic surface memory, an optical memory, and a cloud memory.

Optionally, the data processing module 6103 may also process the data transmitted by the remaining maintenance terminals 300 through their corresponding data transmission modules.

Optionally, the data processing module 6103 preferentially processes the data from the server 100, and then processes the data sent from the remaining maintenance terminals 300.

Optionally, the data visualization display module 6105 further includes an information prompt module. After processing the data from the data storage module 6102, the information prompt module may prompt the maintenance object in different manners to prompt the maintenance object to pay attention to the real-time information more quickly. These include, but are not limited to, a warning light for the maintenance terminal 300, a warning sound for the maintenance terminal 300, and vibration of the maintenance terminal 300. Meanwhile, the maintenance object can set reminding modes of different information through the information prompt module.

The tool analysis module 6104 may analyze the processed fault data, and analyze the maintenance tools required for the maintenance of the maintenance object according to different data migration levels.

For example, when the rotor rotation speed data has small deviation, the condition that oil is added to the bearing is considered, so that the wind driven generator is judged to only need to be subjected to daily maintenance, and a maintenance object is recommended to carry a set of simple dismounting tool;

Recommended content is exemplified as follows:

oiling and replacing the bearing;

universal meter, megger, spanner, screwdriver, power-driven and hand hammer.

When the rotational speed data is greatly shifted, the recommended content may have the following examples:

motor extracting tool: screw driver, iron tongs, wrench, sleeve, hammer, diagonal wrench, chisel, socket head wrench, dual-purpose wrench, puller, etc.;

winding extracting tool: electrician chisel, stainless steel pass through strip, cage motor roaster, small steel wire rod, etc.;

winding tool: the wire drawing machine comprises a motor universal wire drawing die, a wire winding machine, a stainless steel pressing plate, a stainless steel scribing plate, a rubber hammer, scissors, an electrician knife and the like;

detection tool: multimeter, clamp ammeter, megger, etc.

Optionally, the tool analysis module 6104 may consider multiple factors for the type of tool used for the multi-factor fault maintenance, and prevent the situation that the tool carried by the maintenance object is insufficient as much as possible.

Optionally, the visual display manner of the data by the data visual display module 6105 may include a time-division visual display or a real-time visual display.

The time-phased visual display may be displayed using a data visualization technique by accessing data in the data storage module 6102 or processing data in the data storage module 6102. The time-segment visual display may be a data change visual display per minute, a data change visual display per hour, a data change visual display per day, a data change visual display per month, or a data change visual display per year. Display techniques for time-lapse data visualization may include display by a data visualization chart.

Real-time visual display can realize real-time data monitoring through a data visual platform.

Alternatively, the maintenance object may select a presentation manner of the data visualization on the maintenance terminal 300, and may send the presentation result of the data visualization to other maintenance terminals 300 through the data transmission module.

Illustratively, the maintenance terminal 300 receives rotor speed data per second transmitted from the server 100 through the data receiving module 6101 for the last five hours, and then the data receiving module 6101 stores the data to the data storing module 6102. If the maintenance object wants to check the change of the temperature per hour in the past five hours, at this time, the data processing module 6103 invokes the data in the data storage module 6102 and calculates the average value of the temperature per hour, then the data processing module 6103 transmits the processed data to the graph drawing portion in the data visualization display module 6105, and the data visualization display module 6105 presents the data visualization result to the maintenance object through the maintenance terminal 300, and the example visualization graph is shown in fig. 7.

The wind driven generator fault early warning device can be applied to computer equipment, such as a server or terminal equipment. The apparatus embodiments may be implemented by software, or may be implemented by hardware or a combination of hardware and software. Taking software implementation as an example, the device in a logic sense is formed by reading corresponding computer program instructions in the nonvolatile memory into the memory through a processor of the file processing where the device is located. In terms of hardware, as shown in fig. 8, a hardware structure diagram of a computer device where the wind turbine fault early warning device according to the embodiment of the present disclosure is located is shown in fig. 8, and besides the processor 810, the memory 830, the network interface 820, and the nonvolatile memory 840 shown in fig. 8, a server or an electronic device where the wind turbine fault early warning device 831 is located in the embodiment generally may include other hardware according to an actual function of the computer device, which is not described herein again.

Now, for the wind power generator fault early warning method implemented in the present disclosure, there are the following examples:

suppose there are 10 wind generators A, B, C, D, E, F, G, H, I, J somewhere and that these 10 wind generators are in the jurisdiction of a, b, c, d, e five maintenance terminals.

Exemplary, the relative distances between each wind turbine and the maintenance terminal are shown in Table 1 below:

the positions and jurisdictions of 10 wind power generators and 5 maintenance terminals are shown in fig. 9, the relative distances between 10 wind power generators and 5 maintenance terminals are shown in table 1, and real-time data of 10 wind power generators are shown in table 2. Meanwhile, the monitoring data of the wind driven generator are provided with component temperature data, environment wind power data and rotor rotating speed data, wherein the weight of the wind driven generator is 5, 1 and 4 respectively, the temperature standard value of the wind driven generator is 40 ℃, and the swinging interval is [38 ℃,42 ]; the standard value of the environmental wind power is 25m/s, and the swing interval is [20m/s,30m/s ]; the standard value of the rotor rotation speed is 3000/min, and the swing interval is [2900 rpm, 3100 rpm ]. The fault class is divided into five classes, the fault class influence value is divided into one fault class every 0.1 from 0.1, the fault class is 5 classes when the fault class is larger than or equal to 0.5, the fault class judgment value is 3, and the fault class early warning mode is assumed to be consistent with the previous example.

Exemplary, the monitoring data for each wind turbine is shown in table 2 below:

the following analysis is now made for the maintenance measures for each wind turbine:

firstly, calculating the fault grade influence value of each wind driven generator.

A: because the environment wind power is 30m/s in the swinging interval, the environment wind power data does not participate in the calculation of the fault level influence value, and the data in the swinging space are not repeated, namely (65-40) multiplied by 0.5/40=0.3125;

B：（55-40）×0.5/40+（34-25）×0.1/25+（3453-2700）×0.4/3000=0.3239；

C：（40-20）×0.5/40+（3243-2700）×0.4/3000=0.3224；

D：（43-25）×0.1/25+（3000-1167）×0.4/3000=0.3164；

E：（40-35）×0.5/40+（53-30）×0.1/25+（3000-2133）×0.4/3000=0.2701；

F：（60-40）×0.5/40+（32-25）×0.1/25+（3000-2321）×0.4/3000=0.3685；

G：（40-10）×0.5/40+（34-25）×0.1/25+（4452-3000）×0.4/3000=0.6046；

H：（25-13）×0.1/25+（4232-3000）×0.4/3000=0.2123；

I：（72-40）×0.5/40+（34-25）×0.1/25+（3543-3000）×0.4/3000=0.5084；

J：（40-30）×0.5/40+（3000-2342）×0.4/3000=0.2127。

and obtaining the corresponding fault grade of each wind driven generator according to the calculated fault grade influence value. Namely A, B, C, D, E, F, G, H, I, J is three-level, two-level, three-level, five-level, two-level, five-level and two-level respectively.

Since the assumed failure rank determination value is 3, the determined target wind turbine is A, B, C, D, F, G, I.

I.e., a has a jurisdiction of B, C;

b is A, B, D, F in jurisdiction;

c is B, F, I in jurisdiction;

d is C, I in jurisdiction;

e is F, G in jurisdiction.

G. I is the highest failure level but not in the same jurisdiction at the same time, so the repair work of G, H can be done at the same time. G is only in jurisdiction of e, so the server sends notification and fault early warning to maintenance terminal e.

And adopting a corresponding buzzer early warning mode, a corresponding display lamp early warning mode and a corresponding fault information pushing early warning mode according to the fault early warning mode corresponding to the five-level fault level, wherein the color of the display lamp is red. And meanwhile, prompting e to carry a maintenance tool with too low temperature of the maintenance part and too high rotating speed of the rotor according to the fault data type of G.

The target wind power generator I is located in the jurisdiction of the maintenance terminals c and d at the same time, and the distances I to c and the distances I to d are compared according to the table 1. As can be seen from the table, the distance I to c is 9km and the distance I to d is also 9km. At this time, the maintenance terminals c and d are simultaneously sent with maintenance notification, and if one of the servers sends a rejection request, the maintenance notification of I is sent to the other. If both sides send out the confirmation information, the one who sends out the confirmation information first carries out maintenance. The target wind driven generator I is also five stages of fault grades, so that the fault early warning mode adopted by the target wind driven generator I is the same as G.

At this time, assuming that c sends out confirmation information first, the target wind turbine I is maintained by c.

At this time, the fault pre-warning mode of the target wind driven generators adopts a corresponding fault information pushing pre-warning mode, and meanwhile, the color of a display lamp at the target wind driven generator is white.

At this time, only C remains in the target wind power generator in the jurisdiction of the maintenance terminal d, and B and C remain in the jurisdiction of a, so that the target wind power generator C is delivered to d for maintenance, and all the target wind power generators are quickly maintained.

Similarly, the target wind power generator B is delivered to the maintenance terminal a.

For the remaining target wind driven generator A, D, F, the fault grade influence values are compared, F is larger than D and larger than A, and the fault grade influence values of D and A are similar, namely the fault degree is similar. So that F can be assigned to the maintenance terminal c, which, after maintenance I, then goes to maintenance F.

A and D are sent to a maintenance terminal b, and the maintenance is performed on D first and then on A.

And E, J, H, after the maintenance of the target wind driven generator is finished, the maintenance is performed. The warning mode of the display lamp is adopted, and the color of the display lamp is blue.

The implementation process of the functions and roles of each module in the above device is specifically shown in the implementation process of the corresponding steps in the above method, and will not be described herein again.

For the device embodiments, reference is made to the description of the method embodiments for the relevant points, since they essentially correspond to the method embodiments. The apparatus embodiments described above are merely illustrative, wherein the modules illustrated as separate components may or may not be physically separate, and the components shown as modules may or may not be physical, i.e., may be located in one place, or may be distributed over a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the objectives of the disclosed solution. Those of ordinary skill in the art will understand and implement the present invention without undue burden.

The foregoing has described certain embodiments of the present disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any adaptations, uses, or adaptations of the disclosure following the general principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

It is to be understood that the present disclosure is not limited to the precise arrangements and instrumentalities shown in the drawings, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

The foregoing description of the preferred embodiments of the present disclosure is not intended to limit the disclosure, but rather to cover all modifications, equivalents, improvements and alternatives falling within the spirit and principles of the present disclosure.

Claims

1. The wind driven generator fault early warning method is characterized by comprising the following steps of:

acquiring monitoring data;

2. The wind turbine fault pre-warning method according to claim 1, wherein the determining the corresponding fault pre-warning information based on the fault level includes:

3. The wind turbine fault pre-warning method according to claim 1, wherein determining the fault level of the wind turbine according to the monitoring data comprises:

4. A wind turbine fault pre-warning method according to claim 1 or 3, wherein said determining a fault level of the wind turbine based on the monitoring data comprises:

acquiring weight data set for each data type of the monitoring data;

5. The wind power generator fault early warning method according to claim 1, wherein the matching maintenance terminal based on the fault level comprises:

and matching the maintenance terminal according to the maintenance priority.

6. The method for wind turbine fault pre-warning according to claim 5, wherein said ranking said wind turbines by said fault level, determining a maintenance priority for each of said wind turbines, comprises:

obtaining a fault grade judgment value;

7. The wind turbine fault pre-warning method according to claim 5, wherein the matching maintenance terminal based on the fault level comprises:

acquiring positioning information of each maintenance terminal;

and matching the position information and the position coordinates of the wind driven generator belonging to the highest priority to a maintenance terminal closest to the wind driven generator belonging to the highest priority, and sending a maintenance notification to the maintenance terminal.

8. The wind turbine fault pre-warning method of claim 5, further comprising:

9. The wind power generator fault early warning method according to claim 1, wherein the matching maintenance terminal based on the fault level comprises:

10. The utility model provides a aerogenerator trouble early warning device which characterized in that includes:

the data acquisition module is used for acquiring monitoring data;

the fault grade judging module is used for determining the fault grade of the wind driven generator according to the monitoring data;

the fault early warning module determines corresponding fault early warning information based on the fault grade and sends the fault early warning information to each maintenance terminal;

And a maintenance object matching module for determining candidate maintenance terminals responding to the fault early warning information and matching target maintenance terminals for maintaining the wind driven generator in the candidate maintenance terminals based on the fault level.