CN108226775B - Fault self-detection method and device of wind driven generator - Google Patents
Fault self-detection method and device of wind driven generator Download PDFInfo
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- CN108226775B CN108226775B CN201611148516.6A CN201611148516A CN108226775B CN 108226775 B CN108226775 B CN 108226775B CN 201611148516 A CN201611148516 A CN 201611148516A CN 108226775 B CN108226775 B CN 108226775B
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
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Abstract
The invention provides a fault self-detection method and a fault self-detection device of a wind driven generator, wherein the method comprises the following steps: acquiring operation data of the fan after the fan fails in operation; determining component information corresponding to the operation data by using a preset data structure tree; determining fault information of the component with the fault according to the operation data in the determined component information, wherein the fault information comprises at least one of the following information: the number of faults, the cause of the fault and the type of the fault. According to the fault self-detection method and device of the wind driven generator, the operation data of the fan is obtained, the information of the components can be determined by using the data structure tree, and further the fault number, the fault reason, the fault type and the like of the components with faults can be determined according to the operation data, so that the difficulty of fan fault detection is effectively reduced, the time spent on fan troubleshooting is reduced, and the fan fault detection efficiency is improved.
Description
Technical Field
The invention relates to the technical field of wind power, in particular to a fault self-detection method and device of a wind driven generator.
Background
With the rapid development of scientific technology, wind power generation technology is mature day by day, and for wind power generation equipment, as the type selection of the equipment is changed constantly, megawatt-class MW units are configured in various ways, the configuration of the megawatt-class MW units brings much burden to field maintenance personnel, on the same project field, there are possibly several units configured in different ways, and the units configured in different ways may generate different types of faults.
In the prior art, different types of faults may occur to units with different configurations, so that debugging and maintenance personnel are required to have extremely high maintenance capability, and more efforts are required to learn, thereby increasing the difficulty of the service level of the debugging and maintenance personnel; when the unit is out of order during operation, the owner and the ordinary workers need to spend much time for troubleshooting, so that the availability of the unit is influenced, the generating capacity of the unit is greatly influenced, and the owner is greatly damaged.
Disclosure of Invention
The invention provides a fault self-detection method and a fault self-detection device of a wind driven generator, which are used for solving the above or other potential problems in the prior art.
One aspect of the present invention provides a method for self-detecting a fault of a wind turbine, including:
acquiring operation data of a fan after the fan fails in operation;
determining component information corresponding to the operation data by using a preset data structure tree;
determining fault information of a component with a fault according to the operation data in the determined component information, wherein the fault information comprises at least one of the following information: the number of faults, the cause of the fault and the type of the fault.
Another aspect of the present invention provides a fault self-detection apparatus of a wind turbine, including:
the acquisition module is used for acquiring the operation data of the fan after the fan fails in operation;
the processing module is used for determining component information corresponding to the operating data by utilizing a preset data structure tree;
the determining module is used for determining fault information of the component with the fault according to the operation data in the determined component information, wherein the fault information comprises at least one of the following information: the number of faults, the cause of the fault and the type of the fault.
According to the fault self-detection method and device of the wind driven generator, the operation data of the fan is obtained, the component information can be determined by using the data structure tree, and at least one of the fault number, the fault reason and the fault type of the component with the fault can be determined according to the operation data, so that the difficulty of fan fault detection is effectively reduced, the time spent on fan fault troubleshooting is reduced, the fan fault detection efficiency is improved, the practicability of the fault self-detection method is further guaranteed, and the popularization and application of the market are facilitated.
Drawings
Fig. 1 is a schematic flow chart of a fault self-detection method for a wind turbine generator according to an embodiment of the present invention;
fig. 2 is a schematic flowchart of a process of determining component information corresponding to the operation data by using a preset data structure tree according to an embodiment of the present invention;
fig. 3 is a schematic flow chart of a method for self-detecting a fault of a wind turbine according to another embodiment of the present invention;
fig. 4 is a schematic flowchart of a process of determining fault information of a faulty component according to the operation data according to an embodiment of the present invention;
fig. 5 is a schematic flow chart of a fault self-detection method for a wind turbine according to another embodiment of the present invention;
FIG. 6 is a schematic structural diagram of a data structure tree according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a fault self-detection device of a wind turbine according to an embodiment of the present 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.
Fig. 1 is a schematic flow chart of a fault self-detection method for a wind turbine generator according to an embodiment of the present invention; fig. 2 is a schematic flowchart of a process of determining component information corresponding to operating data by using a preset data structure tree according to an embodiment of the present invention; fig. 4 is a schematic flowchart of determining fault information of a faulty component according to operation data according to an embodiment of the present invention; as can be seen from fig. 1-2 and 4, the present embodiment provides a fault self-detection method for a wind turbine generator, which is used for automatically detecting fault information after a fault occurs in the operation of a wind turbine generator, so as to improve the efficiency of detecting the fault of the wind turbine generator; specifically, the fault self-detection method comprises the following steps:
s101: acquiring operation data of the fan after the fan fails in operation;
the embodiment does not limit the specific content of the operation data of the fan, and a person skilled in the art can set the operation data according to specific design requirements, preferably, the operation data of the fan is set to include: running data before the fan fails in operation and before the fan fails in a first preset time period, and running data after the fan fails in operation and after the fan fails in a second preset time period; it should be noted that the first preset time period and the second preset time period are preset, and a person skilled in the art can set specific numerical value ranges of the first preset time period and the second preset time period according to specific design requirements, and in order to improve the detection efficiency of the fan fault, it is more preferable to set the first preset time period to 90s and the second preset time period to 30s, that is, to obtain pre-fault operation data within 90s before the fan fault occurs and post-fault operation data within 30s after the fan fault occurs, while the fan fault self-detection can be realized, the number of the operation data is effectively reduced, and further, the efficiency of the fault self-detection can be improved.
In addition, since there are many parameters related to the operation of the wind turbine, the acquired wind turbine operation data may be set to include: digital quantity information and analog quantity information, wherein the digital quantity information may include: the variation time information (holding time, pre-holding time, post-holding time, etc.) of the trigger edge signal, the high-low voltage signal (specific voltage value), etc., and the analog quantity information may include: ambient temperature and sensor temperature, etc.
In addition, the implementation manner of specifically acquiring the operation data of the fan is not limited in this embodiment, and a person skilled in the art may set the implementation manner according to specific design requirements, for example, the manner of acquiring the data information may be set to be acquired by connecting a wireless router and a processor PLC in the fan, where the PLC is configured to monitor and control the working state of the fan, and after monitoring the data, the PLC is connected with the PLC through the wireless router, and thus the operation data of the fan may be acquired; of course, those skilled in the art may also use other methods to obtain the fan operation data, which are not described herein again.
S102: determining component information corresponding to the operation data by using a preset data structure tree;
the data structure tree is preset data information corresponding to the fan structure; the data structure tree comprises structural characteristic information of each component in the fan; after the operation data is obtained, determining component information related to the operation data according to information characteristics of the operation data, wherein the component information may include characteristic information of one or more components; the specific implementation manner of specifically determining the component information corresponding to the operating data is not limited in this embodiment, and a person skilled in the art may set the component information according to a specific design requirement, and preferably, the determining of the component information corresponding to the operating data by using the preset data structure tree may be specifically set to include:
s1021: acquiring preset identification information in the running data;
the identification information is preset and is used for identifying the components related to the operation data; the identification information may be set in the name of the operation data; for example, the first bit to the second bit in the operation data name may be set as identification information bits, and the identification information may be obtained by obtaining information at the identification information bits.
S1022: and determining component information corresponding to the operating data according to the identification information and by utilizing the corresponding relation between the identification information and the component information stored in the data structure tree.
It should be noted that the identification information stored in the data structure tree does not correspond to the component information one by one, that is, one identification information may correspond to a plurality of components, and one component may also correspond to a plurality of identification information; that is, one of the operation data may correspond to a plurality of components, and one component may also correspond to a plurality of data; after the identification information is acquired, the component information corresponding to the operation data can be determined according to the corresponding relationship between the identification information and the component information.
S103: determining fault information of the component with the fault according to the operation data in the determined component information, wherein the fault information comprises at least one of the following information: the number of faults, the cause of the fault and the type of the fault.
After determining corresponding component information, analysis processing can be performed on the operation data, so that fault information of a component with a fault can be determined, the implementation manner of determining the fault information of the component with the fault is not limited in this embodiment, and a person skilled in the art can set the fault information according to specific design requirements, and preferably, the determination of the fault information of the component with the fault according to the operation data is set to specifically include:
s1031: analyzing and comparing the operation data with preset threshold data;
the threshold data is preset, different threshold data can be provided for different operation data of the components, the threshold data can include maximum threshold data, minimum threshold data or threshold intervals and the like, and after corresponding component information is determined, the operation data of each component can be analyzed and compared with the threshold data, so that whether the component is in fault during operation is determined according to the analysis and comparison result.
S1032: if the operation data exceeds the range of the threshold data, confirming that the operation of the component has a fault;
when the analysis and comparison result shows that the operation data exceeds the range of the threshold data, namely the operation data is possibly larger than the maximum threshold data, or the operation data is smaller than the minimum threshold data, and the like, the component at the moment exceeds the data range of normal operation, and the component can be confirmed to be in fault during operation.
It can be understood that, when the analysis and comparison result indicates that the operation data satisfies the range of the threshold data, the component is in the normal operation range at this time, and therefore it can be determined that the component is faulty.
S1033: determining the fault information of the component according to the operation data by using a preset fault information base;
the fault information base stores the corresponding relation between the operation data and the fault information.
After the operation of the component is confirmed to be failed, the corresponding relation between the operation data and the failure information is stored in the failure information base, so that the failure information of the component can be searched in the failure information base by utilizing the corresponding relation; it should be noted that the correspondence between the operation data and the fault information stored in the fault information base is a non-consistent correspondence, that is, one operation data may correspond to a plurality of fault information, and one fault information may also correspond to a plurality of operation data; therefore, a plurality of fault information of the components can be acquired according to one operation data, and the fault information includes at least one of the following information: the number of faults, the cause of the fault and the type of the fault.
According to the fault self-detection method of the wind driven generator, the operation data of the fan is obtained, the information of the components can be determined by using the data structure tree, and at least one of the fault number, the fault reason and the fault type of the component with the fault can be determined according to the operation data, so that the difficulty of fan fault detection is effectively reduced, the time spent on fan troubleshooting is reduced, the detection efficiency of the fan fault is improved, the practicability of the fault self-detection method is further guaranteed, and the method is favorable for popularization and application in the market.
Fig. 3 is a schematic flow chart of a method for self-detecting a fault of a wind turbine according to another embodiment of the present invention; FIG. 6 is a schematic structural diagram of a data structure tree according to an embodiment of the present invention; on the basis of the foregoing embodiment, with reference to fig. 1 to 4 and fig. 6, it can be seen that, in this embodiment, a specific establishment manner of the data structure tree is not limited, and a person skilled in the art may set the method according to a specific design requirement, and preferably, before determining the component information corresponding to the operating data by using the preset data structure tree, the method is further configured to:
s201: acquiring structural characteristic information of each component in the fan;
the structural characteristic information comprises the connection relation, the setting position, the function and the like among all the components, and after the structural characteristic information is acquired, the data structure tree can be established according to the structural characteristic information, so that the established data structure tree corresponds to all the components in the fan.
S202: determining the connection relation and the level information of each component according to the structural characteristic information;
in order to facilitate the data structure tree to correspond to each real component in the fan, after the structural characteristic information is obtained, the connection relation and the level information of each component can be determined according to the structural characteristic information; the level information can be obtained by analyzing according to the function and the setting position of the component.
S203: and establishing a data structure tree corresponding to each component in the fan according to the connection relation and the level information of each component.
After the connection relationship and the level information are obtained, a data structure tree corresponding to each component in the fan may be established according to the two pieces of information, and in order to more clearly understand the technical scheme of the embodiment, the following specific embodiments are exemplified:
establishing a data structure tree corresponding to an electric control system in the fan, wherein the fault structure tree is to divide the electric control system step by step according to the device characteristics until a specific component or a certain important parameter of unit operation; specifically, the method comprises the following steps: the general electric control system of the fan includes: the system comprises a main control system, a water cooling system, a pitch control system and a converter system, wherein the main control system further comprises a tower bottom system and a tower system, the tower bottom system further comprises a tower bottom UPS, a main control cabinet, a transformer and other communication devices, and the tower bottom UPS can be further arranged to comprise: the power manager, the storage battery and the like, therefore, the data information can be classified according to the structure of stepwise refining the main control system, as shown in fig. 6, so that each data information corresponds to a specific component, however, by analyzing and judging the data information, specific components can be determined to have faults, fault reasons and fault type information of the faults, and the like.
The structural characteristic information of each component in the fan is acquired, the connection relation and the level information of each component are determined according to the structural characteristic information, and then the data structure tree corresponding to each component in the fan is established according to the connection relation and the level information, so that the stability and the reliability of the establishment of the data structure tree are effectively ensured, further, when the data structure tree is used for analyzing and processing fan faults, each component in the fan can be traced back, the detection quality and the efficiency of the fault self-detection method are further improved, and the stability and the reliability of the use of the fault self-detection method are ensured.
Fig. 5 is a schematic flow chart of a fault self-detection method for a wind turbine according to another embodiment of the present invention; on the basis of the foregoing embodiment, as can be seen with reference to fig. 1 to 6, after determining the fault information of the component according to the operation data by using the preset fault information base, the method of this embodiment is configured to further include:
s301: determining a fault processing strategy corresponding to the fault information according to the corresponding relation between the fault information stored in the fault information base and the fault processing strategy;
after the fault information is determined, in order to further facilitate maintenance and management of the faulty fan by a worker, a corresponding relationship between the fault information and the fault handling policy is stored in the fault information base in advance, and it should be noted that the fault information and the fault handling policy are not in a one-to-one correspondence relationship, that is, one fault information may correspond to a plurality of fault handling policies, and one fault handling policy may correspond to a plurality of fault information.
S302: and displaying the fault information and a fault processing strategy corresponding to the fault information.
After the fault handling strategies are acquired, the fault handling strategies can be displayed, and when the acquired fault handling strategies are multiple, the fault handling strategies can be arranged and displayed according to a preset priority order, wherein the fault handling strategy with the highest probability of solving the fault is preferentially displayed; specifically, the fault processing strategy can be displayed through the wireless panel, so that a user or a worker can directly obtain the process and the result of analyzing and processing the data information, the user or the worker can perform fault troubleshooting operation according to the displayed fault processing strategy, the service level difficulty of debugging and maintenance personnel is effectively reduced, the maintenance and management time is shortened, the generated energy of a fan is ensured, the practicability of the fault self-detection method is improved, and the popularization and the application of the market are facilitated.
In specific application, the following description will be given by taking the selection of relevant reference variables of the UPS as an example:
after the operational data of the fan is acquired, the operational data is analyzed and identified, specifically, the operational data can be determined to be the data information corresponding to the UPS by identifying the special identification information in the operational data, after the operational data is determined to be the data information corresponding to the UPS, the operational data can be further analyzed and processed, whether the operational fault occurs in the fan is judged according to the analysis and processing result, and if the operational fault occurs, the main control UPS includes: the power manager and the storage battery specifically confirm that the main control UPS of the fan breaks down, and the main control UPS breaks down to show that: the power manager fails, and the main cabinet UPS battery warns at the moment, so that the failure reason and the failure information can be accurately found.
In addition, in order to more clearly understand a specific implementation process of determining fault information of a faulty component according to operation data in the present application, the following specific embodiments are illustrated:
because the operating data comprises a plurality of reference variables, in order to analyze the reference variables, the reference variables can be divided into digital quantity data and analog quantity data, and both the digital quantity data and the analog quantity data comprise corresponding fault mechanism description information, so that corresponding fault points and corresponding fault information can be confirmed according to analysis and judgment of the reference variables. Specifically, the method comprises the following steps:
firstly, according to the characteristics of digital quantity and analog quantity data change, dividing fault mechanisms according to digital quantity and analog quantity, and specifically dividing the fault mechanisms into the following categories:
(1) trigger edge class: a failure mechanism for the digital quantity reference variable;
(2) longitudinal variation class: a fault mechanism for the analog reference variable;
(3) the lateral variation class: a failure mechanism for analog and digital reference variables;
(4) limit class: failure mechanism for analog reference variables.
It should be noted that, in the process of analyzing the fault parameters, different strategies may be adopted according to the classification of the parameters, for example: the horizontal analysis process can be analysis and judgment on data volume information of the same parameter at different moments, and the longitudinal analysis process is as follows: analyzing and judging data information with different parameters at the same time; the limit classes are: and analyzing and comparing the data information of a certain parameter at a certain moment with preset standard threshold information, and the like.
For the data information of the trigger edge class, during analysis and comparison, the type and the time characteristic of the trigger edge are mainly analyzed and determined, for example, the trigger edge may be divided into: rising edge, falling edge, holding low, holding high, no state change, and rising or falling edge, and the temporal characteristics may generally include: the method comprises the steps that the trigger edge holding time, the trigger edge front holding time, the trigger edge rear holding time and the like are respectively provided with different corresponding time characteristic parameters for different types of trigger edge data information, each time characteristic parameter can be provided with a preset standard threshold value during analysis, and whether the fan breaks down or not can be determined according to the data information of the trigger edges by analyzing and comparing the acquired time characteristic parameters with the standard threshold values.
For the data information of the longitudinal variation class, when analyzing and comparing, analyzing and judging the time characteristic, wherein the longitudinal variation class refers to the variation trend of the same parameter in the longitudinal period, so that the longitudinal period needs to be acquired, the longitudinal variation in the longitudinal period can be acquired, and whether the fan breaks down or not can be judged according to the data information of the longitudinal variation class by analyzing and comparing the longitudinal variation with a preset threshold; further, when the longitudinal variation is 0, the longitudinal holding time is acquired, and whether the fan breaks down or not is judged by analyzing and judging the longitudinal holding time and a preset time threshold.
For the data information of the transverse variation class, during analysis and comparison, the data information is similar to the data information of the longitudinal variation class, specifically, the data variation in the transverse period is analyzed and judged, so that the transverse period needs to be acquired, the transverse variation of each parameter in the transverse period is acquired, and whether the fan fails or not can be judged according to the data information of the transverse variation by analyzing and comparing the transverse variation with a preset threshold; further, when the transverse variation of a certain parameter is 0, the transverse holding time is acquired, and whether the fan breaks down or not is judged by analyzing and judging the transverse holding time and a preset time threshold.
When the data information of the limitation type is analyzed, a maximum threshold and a minimum threshold corresponding to the parameter when the fan works normally exist in each parameter during the operation, so that the data information of the display type is respectively compared with the preset maximum threshold and the preset minimum threshold, and if the preset condition is not met, the fan can be determined to have a fault.
In addition, when the fault information includes a plurality of categories of reference variables, for example, including a trigger edge category, a longitudinal variation category and a transverse variation category, when the trigger edge category information is analyzed and judged, the fault point that may be confirmed is a and the corresponding fault information a1, when the longitudinal variation category information is analyzed and judged, the fault point that may be confirmed is B and the corresponding fault information B1, when the transverse variation category information is analyzed and judged, the fault point that may be confirmed is C and the corresponding fault information C1, when the fault information is displayed, the fault point a/B/C and the corresponding fault information are both displayed, that is: more than one fault point can be obtained, if several fault parameters meet the fault mechanism of the fault point, multiple fault analysis results can occur, and a user needs to sequentially troubleshoot the fault points.
Each type of mechanism corresponds to a structure of data change attributes (hereinafter referred to as mechanism attribute structure) as shown in table 1 below;
table 1 mechanism attribute structure:
after determining the characteristics of the operating data (determining whether the operating data is digital data or analog data), analyzing and processing the data information according to the corresponding analysis process to determine whether the fan fails, and in addition, the specific time duration of the horizontal period and the vertical period is not limited, and a person skilled in the art can set the periods according to specific design requirements, wherein, more preferably, the vertical period and the horizontal period can be set to be integral multiples of 20ms, so as to improve the accuracy of analyzing and determining the data information.
Further, for the operation data of the trigger edge class, the related information of the falling edge may be obtained, and the specific information is shown in the following table:
table 2: falling edge trigger case
Description of the failure mechanism: if the retention time is more than Ts after the data information is analyzed and processed and the feedback signal of the switch is lost or jittered (falling edge), T can be 10s, 15s or 20s, etc.; it can be determined that a "XXX fuse feedback loss" fault has occurred, and the fault mechanism output triggers the number of edge faults and the cause of the fault because:
1: XXX air open feedback fault;
2: the digital quantity module is damaged;
3: the feedback signal line is broken.
Through the determined fault information, a corresponding fault handling strategy can be determined, and specifically, a corresponding fault description and handling method comprises the following steps:
1: checking whether the air switch XXX is tripped or not, if the air switch XXX is not tripped, checking whether the contact wiring of the feedback contact XXX is loose or not, and if the contact is normally in a closed state, checking whether the feedback loop wiring is loose or not.
2: if 24VDC exists in the 1 port of the digital input module of the measuring substation, and the fault cannot be reset, the digital input module is damaged, and the digital input module is required to be replaced.
3: if the contact wiring of the air switch XXX is not problematic and has 24VDC, the 1 port of the substation voltage-multiplying digital input module does not have 24VDC, which indicates that the feedback signal line is damaged, please find the damaged point of the cable.
At the moment, the user or the staff can process the wind turbine generator according to the displayed fault processing strategy so that the fan returns to the normal working state.
In addition, for the operation data of the trigger edge class, the related information of the falling edge can be obtained, and the specific information is shown in the following table:
table 3: rising edge trigger case
Description of the failure mechanism: if the retention time is longer than T1s, T1 can take 2s, 3s or 4s, etc. after the data information is analyzed and processed, and the low voltage crossing flag bit (rising edge) is triggered, it can be determined that the "voltage low" fault occurs, and then the fault mechanism outputs the trigger edge fault point:
a voltage ride through fault.
Through the determined fault point and fault information, a corresponding fault processing strategy can be determined, and specifically, a corresponding fault description and processing method comprises the following steps: if the voltage drop time exceeds a limit value T1s (for example, 2s), the unit cannot complete crossing; or when continuous low-voltage ride through occurs, the low-voltage ride through cannot be completed, and the unit reports a low-voltage fault of a power grid.
It should be noted that specific judgment contents of other types of fault information and fault handling policies are not limited, and those skilled in the art may set the fault information and the fault handling policies according to specific design requirements, or may set the fault information and the fault handling policies in the same or similar manner as the above table, which is not described herein again.
And finally, displaying the determined fault information and the fault processing strategy, for example, according to the table, so that a user or a worker can process the wind turbine generator according to the displayed fault processing strategy, the fan returns to a normal working state, the efficiency of searching the fault information is effectively improved, and the stability and the reliability of the operation of the fan are ensured.
Fig. 7 is a schematic structural diagram of a fault self-detection device of a wind turbine generator according to an embodiment of the present invention, and referring to fig. 7, the present embodiment provides a fault self-detection device of a wind turbine generator, where the fault self-detection device may perform a fault self-detection method on a wind turbine generator, and specifically, the fault self-detection device includes:
the acquisition module 1 is used for acquiring the operation data of the fan after the fan fails in operation;
wherein, the operational data of fan includes: the method comprises the steps of running data before the fault occurs in the first preset time period before the fan runs into fault, and running data after the fault occurs in the second preset time period after the fan runs into fault.
The processing module 2 is used for determining component information corresponding to the operation data by utilizing a preset data structure tree;
in this embodiment, the specific implementation manner of the processing module 2 determining the component information corresponding to the operating data by using the preset data structure tree is not limited, and a person skilled in the art can set the processing module 2 according to a specific design requirement, and preferably, the processing module is set to specifically:
acquiring preset identification information in the running data;
and determining component information corresponding to the operating data according to the identification information and by utilizing the correspondence between the identification information and the component information stored in the data structure tree.
The determining module 3 is configured to determine, in the determined component information, fault information of a component having a fault according to the operation data, where the fault information includes at least one of the following information: the number of faults, the cause of the fault and the type of the fault.
The embodiment does not limit the specific implementation manner of determining the fault information of the faulty component by the determining module 3 according to the operating data, and a person skilled in the art can set the fault information according to specific design requirements, and preferably, the device is further configured to include: the fault information base 6 is used for storing the corresponding relation between the operation data and the fault information;
further, the determining module 3 is configured to specifically:
analyzing and comparing the operation data with preset threshold data;
if the operation data exceeds the range of the threshold data, confirming that the operation of the component has a fault;
determining the fault information of the component according to the operation data by utilizing a preset fault information base 6;
the fault information base 6 stores therein a correspondence between the operation data and the fault information.
In this embodiment, specific shape structures of the obtaining module 1, the processing module 2, and the determining module 3 are not limited, and those skilled in the art may set the shape structures according to specific design requirements, which is not described herein again; in addition, the specific implementation process and implementation effect of the operation steps implemented by the obtaining module 1, the processing module 2, and the determining module 3 in this embodiment are the same as the specific implementation process and implementation effect of S101 to S103, S1021 to S1022, and S1031 to S1033 in the foregoing embodiment, and specific reference may be made to the above statements, and details are not described herein again.
The utility model provides a aerogenerator's trouble is from detection device, the operation data that acquire the fan through acquisition module 1 and processing module 2 and utilize the data structure tree can confirm the components and parts information, and then confirm module 3 can confirm at least one in the trouble number, the trouble reason and the fault type of the components and parts that break down according to the operation data, the degree of difficulty of fan fault detection has been reduced effectively, and reduced the time that the trouble needs to be spent to the fan troubleshooting, the detection efficiency to the fan trouble is improved, the practicality of this trouble is from detection device has further been guaranteed, be favorable to the popularization and the application in market.
On the basis of the foregoing embodiment, with reference to fig. 7, it can be seen that, in this embodiment, a specific establishment manner of the data structure tree is not limited, and a person skilled in the art may set the data structure tree according to a specific design requirement, and preferably, the obtaining module 1 and the processing module 2 are set to perform the following operations: in particular, the method comprises the following steps of,
the acquisition module 1 is further configured to acquire structural characteristic information of each component in the fan before determining component information corresponding to the operational data by using a preset data structure tree;
the processing module 2 is further used for determining the connection relation and the level information of each component according to the structural characteristic information;
further, the device is set to further comprise;
and the establishing module 4 is used for establishing a data structure tree corresponding to each component in the fan according to the connection relation and the level information of each component.
The specific shape and structure of the building module 4 are not limited in this embodiment, and those skilled in the art can set the building module according to specific design requirements, which are not described herein again; in addition, in this embodiment, specific implementation processes and implementation effects of the operation steps implemented by the obtaining module 1, the processing module 2, and the establishing module 4 are the same as those of S201 to S203 in the above embodiment, and specific reference may be made to the above statements, which are not described herein again.
On the basis of the above embodiment, as can be seen with reference to fig. 7, the present embodiment configures the processing module 2 to:
determining a fault processing strategy corresponding to the fault information according to the corresponding relation between the fault information stored in the fault information base 6 and the fault processing strategy;
further, the apparatus is configured to further include:
and the display module 5 is used for displaying the fault information and the fault processing strategy corresponding to the fault information.
In this embodiment, a specific shape and structure of the display module 5 are not limited, and a person skilled in the art may set the display module 5 according to specific design requirements, for example, the display module may be set as a display screen, a display interface of an intelligent terminal or a terminal, and the like, as long as the display of related information is achieved, which is not described herein again; in addition, the specific implementation process and implementation effect of the operation steps implemented by the processing module 2 and the display module 5 in this embodiment are the same as the specific implementation processes and implementation effects of S301 to S302 in the above embodiment, and the above statements may be specifically referred to, and are not repeated herein.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
It is obvious to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to perform all or part of the above described functions. For the specific working process of the device described above, reference may be made to the corresponding process in the foregoing method embodiment, which is not described herein again.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A fault self-detection method of a wind driven generator is characterized by comprising the following steps:
acquiring operation data of a fan after the fan fails in operation;
determining component information corresponding to the operation data by using a preset data structure tree;
determining fault information of a component with a fault according to the operation data in the determined component information, wherein the fault information comprises at least one of the following information: the number of faults, the reasons of the faults and the types of the faults;
the operational data of the fan includes: the method comprises the steps of running data before the fan fails in operation and before the fan fails in a first preset time period, and running data after the fan fails in operation and after the fan fails in a second preset time period.
2. The method according to claim 1, wherein determining component information corresponding to the operational data using a preset data structure tree specifically includes:
acquiring preset identification information in the operating data;
and determining component information corresponding to the operating data according to the identification information and by utilizing the corresponding relation between the identification information and the component information stored in the data structure tree.
3. The method according to claim 1 or 2, wherein before determining the component information corresponding to the operation data using a preset data structure tree, the method further comprises:
acquiring structural characteristic information of each component in the fan;
determining the connection relation and the level information of each component according to the structural characteristic information;
and establishing the data structure tree corresponding to each component in the fan according to the connection relation and the level information of each component.
4. The method according to claim 3, wherein determining fault information of the faulty component from the operational data specifically comprises:
analyzing and comparing the operation data with preset threshold data;
if the operation data exceeds the range of the threshold data, confirming that the component is in fault during operation;
determining the fault information of the component according to the operation data by using a preset fault information base;
and the fault information base stores the corresponding relation between the operation data and the fault information.
5. The method of claim 4, wherein after determining the fault information of the component according to the operation data by using a preset fault information base, the method further comprises:
determining a fault processing strategy corresponding to the fault information according to the corresponding relation between the fault information stored in the fault information base and the fault processing strategy;
and displaying the fault information and a fault processing strategy corresponding to the fault information.
6. A fault self-detection device of a wind power generator, comprising:
the acquisition module is used for acquiring the operation data of the fan after the fan fails in operation;
the processing module is used for determining component information corresponding to the operating data by utilizing a preset data structure tree;
the determining module is used for determining fault information of the component with the fault according to the operation data in the determined component information, wherein the fault information comprises at least one of the following information: the number of faults, the reasons of the faults and the types of the faults;
the operational data of the fan includes: the method comprises the steps of running data before the fan fails in operation and before the fan fails in a first preset time period, and running data after the fan fails in operation and after the fan fails in a second preset time period.
7. The apparatus of claim 6, wherein the processing module is specifically configured to:
acquiring preset identification information in the operating data;
and determining component information corresponding to the operating data according to the identification information and by utilizing the corresponding relation between the identification information and the component information stored in the data structure tree.
8. The apparatus of claim 6,
the acquisition module is further used for acquiring structural characteristic information of each component in the fan before determining component information corresponding to the operation data by using a preset data structure tree;
the processing module is further used for determining the connection relation and the level information of each component according to the structural characteristic information;
the device further comprises;
and the establishing module is used for establishing the data structure tree corresponding to each component in the fan according to the connection relation and the level information of each component.
9. The apparatus of claim 8, further comprising: the fault information base is used for storing the corresponding relation between the operation data and the fault information;
the determining module is specifically configured to: analyzing and comparing the operation data with preset threshold data; if the operation data exceeds the range of the threshold data, confirming that the component is in fault during operation; and determining the fault information of the component by using the fault information base and according to the operation data.
10. The apparatus of claim 9,
the processing module is further used for determining a fault processing strategy corresponding to the fault information according to the corresponding relation between the fault information stored in the fault information base and the fault processing strategy;
the device further comprises:
and the display module is used for displaying the fault information and the fault processing strategy corresponding to the fault information.
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| CN109240053B (en) * | 2018-11-16 | 2021-09-07 | 珠海奔图电子有限公司 | Power supply control apparatus, method and image forming apparatus |
| CN109948260B (en) * | 2019-03-22 | 2023-08-01 | 中车大连机车车辆有限公司 | Method, device, equipment and readable storage medium for determining diesel engine repair strategy |
| CN113408078A (en) * | 2021-07-14 | 2021-09-17 | 北京广利核系统工程有限公司 | Control system analysis method and device |
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| US8326577B2 (en) * | 2011-09-20 | 2012-12-04 | General Electric Company | System and method for predicting wind turbine component failures |
| CN102363969A (en) * | 2011-10-14 | 2012-02-29 | 中联重科股份有限公司 | Excavator and method and system for determining equipment failure |
| CN103020436B (en) * | 2012-11-30 | 2015-08-12 | 工业和信息化部电子第五研究所 | Component failure zero analytical approach and system |
| CN103217291B (en) * | 2013-01-06 | 2016-05-04 | 国电联合动力技术有限公司 | A kind of wind power generating set method for diagnosing faults and system |
| CN104123407B (en) * | 2014-06-19 | 2017-04-05 | 电子科技大学 | A kind of testability model auto-creating method based on circuit simulation |
| CN104376033B (en) * | 2014-08-01 | 2017-10-24 | 中国人民解放军装甲兵工程学院 | A kind of method for diagnosing faults based on fault tree and database technology |
| CN106557773B (en) * | 2015-09-25 | 2020-04-24 | 北京宝沃汽车有限公司 | Vehicle fault diagnosis method and system |
| CN106050580B (en) * | 2016-08-17 | 2018-10-23 | 国电联合动力技术有限公司 | A kind of driving chain of wind generating set fault diagnosis method and system |
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