CN108957315A - Fault diagnosis method and equipment for wind generating set - Google Patents
Fault diagnosis method and equipment for wind generating set Download PDFInfo
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- CN108957315A CN108957315A CN201710362949.XA CN201710362949A CN108957315A CN 108957315 A CN108957315 A CN 108957315A CN 201710362949 A CN201710362949 A CN 201710362949A CN 108957315 A CN108957315 A CN 108957315A
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- 238000000034 method Methods 0.000 title claims abstract description 40
- 238000003745 diagnosis Methods 0.000 title claims abstract description 29
- 238000012360 testing method Methods 0.000 claims abstract description 272
- 239000011159 matrix material Substances 0.000 claims abstract description 107
- 238000001514 detection method Methods 0.000 claims abstract description 80
- 238000012544 monitoring process Methods 0.000 claims description 69
- 238000002955 isolation Methods 0.000 claims description 63
- 238000004458 analytical method Methods 0.000 claims description 10
- 238000004590 computer program Methods 0.000 claims description 7
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/34—Testing dynamo-electric machines
- G01R31/343—Testing dynamo-electric machines in operation
Abstract
The invention provides a fault diagnosis method and equipment of a wind generating set, wherein the fault diagnosis method comprises the following steps: determining a system structure of a functional system to be diagnosed of the wind generating set; determining a component to be monitored among the components of the system architecture; establishing a fault and test correlation matrix model according to the information flow direction among all parts to be monitored in the system structure; determining a fault detection test point of the functional system to be diagnosed according to the fault and test correlation matrix model; and detecting the test signal of the fault detection test point, and determining the fault of the functional system to be diagnosed according to the detected test signal. According to the fault diagnosis method and the fault diagnosis device for the wind generating set, the test point for fault detection can be determined according to the matrix model of the correlation between the fault and the test, so that the fault of the functional system to be diagnosed can be rapidly determined by detecting the test signal of the test point for fault detection.
Description
Technical field
The present invention relates to the technical fields of field wind-power electricity generation.More particularly, the failure for being related to wind power generating set is examined
Disconnected method and apparatus.
Background technique
Wind energy is increasingly taken seriously as a kind of clean renewable energy.The installation amount of wind power generating set is year by year
Rise, ratio shared by wind-power electricity generation is increasing, and wind energy has been increasingly becoming a kind of conventional energy resource.With wind power generating set
The increase of quantity and the increase for using the cumulative time, the failure rate of wind power generating set itself also accordingly increase, these failures
It is distributed in unit among each function system.The generation of one failure can generate series of security movement, therefore, improve judgement machine
Group failure, the efficiency of investigation unit hidden danger directly determines the utilization rate of unit rapidly, or even influences entire wind power plant
Generated energy.And in the prior art, wind power generating set needs manually to check and diagnose fault after breaking down, cannot be fast
Unit failure is judged fastly, so that unit hidden danger cannot be checked promptly.
Summary of the invention
The purpose of the present invention is to provide it is a kind of can quick diagnosis function system to be diagnosed whether break down to wind-force
The method for diagnosing faults and equipment of generating set.
An aspect of of the present present invention provides a kind of method for diagnosing faults of wind power generating set, the method for diagnosing faults packet
It includes: determining the system structure of the function system to be diagnosed of wind power generating set；Determination is undetermined in the component of the system structure
Monitoring component；It is related to test that failure is established according to the directions of information flow between monitoring component undetermined each in the system structure
Property matrix model；Determine that the fault detection of the function system to be diagnosed is used according to the failure and test correlation matrix model
Test point；The test signal of the fault detection test point is detected, and function to be diagnosed is determined according to the test signal detected
The failure of energy system.
Another aspect of the present invention provides a kind of failure diagnosis apparatus of wind power generating set, and failure diagnosis apparatus includes:
System structure determines program module, determines the system structure of the function system to be diagnosed of wind power generating set；Element determines program
Module determines monitoring component undetermined in the component of the system structure；Model-builder program module, according to the system structure
In directions of information flow between each monitoring component undetermined establish failure and test correlation matrix model；Detection test point is true
Determine program module, determines that the fault detection of the function system to be diagnosed is used according to the failure and test correlation matrix model
Test point；Program module is detected, detects the test signal of the fault detection test point, and according to the test signal detected
Determine the failure of function system to be diagnosed.
Another aspect of the present invention provides a kind of computer readable storage medium, which has
Computer program, the computer program are configured as that the processor of computer is made to execute above-mentioned method for diagnosing faults.
Another aspect of the present invention provides a kind of including above-mentioned computer readable storage medium computer.
The method for diagnosing faults and equipment of the wind power generating set of embodiment according to the present invention, can be according to failure and test
Correlation matrix model determines fault detection test point, so as to pass through the test signal of detection fault detection test point
Quickly to determine the failure of function system to be diagnosed.
In addition, the method for diagnosing faults and equipment of the wind power generating set of embodiment according to the present invention, it can be according to failure
Fault Isolation test point is determined with test correlation matrix model, so as to pass through the survey of detection Fault Isolation test point
Trial signal is quickly positioned to treat the failure that diagnostic function system has occurred.
Part in following description is illustrated into the other aspect and/or advantage of the present invention, some is by retouching
Stating will be apparent, or can learn by implementation of the invention.
Detailed description of the invention
By the detailed description carried out below in conjunction with the accompanying drawings, above and other objects of the present invention, features and advantages will
It becomes more fully apparent, in which:
Fig. 1 is the method for diagnosing faults for showing the wind power generating set of embodiment according to the present invention；
Fig. 2 shows the examples of the information flow model of embodiment according to the present invention；
Fig. 3 shows the failure and test correlation matrix model of the foundation of information flow model according to Fig.2,；
Fig. 4 shows the flow chart of the step of determination fault detection test point of embodiment according to the present invention；
Fig. 5 shows the flow chart of the step of determination Fault Isolation test point of embodiment according to the present invention；
Fig. 6 is the block diagram for showing the failure diagnosis apparatus of wind power generating set of embodiment according to the present invention.
Specific embodiment
Now, different example embodiments is more fully described with reference to the accompanying drawings.
Fig. 1 is the method for diagnosing faults for showing the wind power generating set of embodiment according to the present invention.Failure shown in FIG. 1
Whether the function system that diagnostic method is applicable to diagnosis wind power generating set breaks down.The wind power generating set includes more
A function system, such as: yaw system, pitch-controlled system and converter system etc..Each function system packet in wind power generating set
Include component relevant to the function of the function system is realized.
Referring to Fig.1, in step S10, the system structure of the function system to be diagnosed of wind power generating set is determined.The follow-up
Disconnected function system refers to wait diagnose the function system whether to break down.The system structure of the function system to be diagnosed refer to
Realize the system structure of the relevant component composition of the function of function system to be diagnosed, which includes mechanical part and electrical member
Part.
In step S20, monitoring component undetermined is determined in the component of the system structure.The monitoring component undetermined refers to
It may cause the component that function system to be diagnosed breaks down.It is appreciated that for the electric component with multiple contacts, example
Such as, contactor may include that main contacts and auxiliary contact can will take part in the electricity of the system structure in an embodiment of the present invention
Each contact of gas control is considered as a component.
Here, whole part or part components in the component of the system structure can be determined as monitoring component undetermined.
For example, whole components in the component of the system structure can be determined as monitoring portion undetermined when system structure is relatively simple
Part.It, can be according to various failure analysis methods by the portion in the component of the system structure when the system structure is complex
Sub-unit is determined as monitoring component undetermined, to reduce the calculation amount of subsequent step.
Preferably, in step S20, come to determine prison undetermined in the component of the system structure in combination with Fault Tree Analysis
Survey component.Specifically, in the component of the system structure, the function system progress event to be diagnosed according to the system structure
Fault tree analysis is to be determined to the failure associated components for causing the function system to be diagnosed to break down；It is related in the failure
Monitoring component undetermined is determined in component.
Here, whole part or part components in the failure associated components can be determined as monitoring component undetermined.Example
Such as, when system structure is relatively simple, whole components in the failure associated components can be determined as monitoring component undetermined.?
When the system structure is complex, the section components in the failure associated components can be determined according to various analysis methods
For monitoring component undetermined, to reduce the calculation amount of subsequent step.
Preferably, in step S20, the section components in the failure associated components can also be determined by following steps
For monitoring component undetermined: obtaining the historical failure data of the function system to be diagnosed；It is determined according to the historical failure data
The failure proportion of each failure associated components, wherein the failure proportion of each failure associated components is by described every
The historical failure number of function system to be diagnosed and the ratio of historical failure total degree caused by a failure associated components；It will
Failure proportion in the failure associated components is greater than the failure associated components of predetermined value as monitoring component undetermined.
In step S30, failure is established according to the directions of information flow between monitoring component undetermined each in the system structure
With test correlation matrix model.
Here, the system first can be established according to the directions of information flow between monitoring component undetermined each in the system structure
The information flow model for structure of uniting establishes failure and test correlation matrix model further according to the information flow model.The information flow
Model embodies the directions of information flow between each monitoring component undetermined.Fig. 2 shows the information of embodiment according to the present invention
The example of flow model.As shown in Fig. 2, the symbol (such as F1, F2, F3 and F4) in box indicates that monitoring component undetermined, arrow indicate
Directions of information flow.
The failure and test correlation matrix model refer to that the correlation logic between faults source and test point closes
The Boolean matrix of system.Particularly, in the Boolean matrix, all elements are logical value (such as 0 or 1).In the Boolean matrix
In, row corresponds to the source of trouble, and column correspond to test point.The element representation element in the Boolean matrix is expert at corresponding failure
When source is broken down, whether the corresponding test point of column where the element can test the fault message of the source of trouble.The element
Indicate that the test point cannot test the fault message of the source of trouble when being 0, which indicates that the test point can test when being 1
The fault message of the source of trouble.
In an embodiment of the present invention, the failure and test correlation matrix model the source of trouble include it is described it is each to
Determine monitoring component, the failure is with the test point in test correlation matrix model for testing and each monitoring component phase undetermined
The output signal of pass.Here, output signal relevant to each monitoring component undetermined, which refers to, can embody each monitoring component undetermined
Whether out of order signal.The case where being electrical component for monitoring component undetermined, which refers to electrical component sheet
The output signal of body；The case where being mechanical part for monitoring component undetermined, which refers to for detecting the Machinery Ministry
The output signal of the sensor of the state of part.
Fig. 3 shows the failure and test correlation matrix model of the foundation of information flow model according to Fig.2,.Such as Fig. 2 and
Shown in Fig. 3, T1, T2, T3 and T4 indicate each test point, each source of trouble F1, F2 of element representation in Boolean matrix shown in Fig. 3,
Whether the fault message of F3 and F4 can be tested in each test point T1, T2, T3 and T4 is arrived.
After establishing the failure and test correlation matrix model, in order to reduce the calculation amount of subsequent step, may be used also
The failure and test correlation matrix model are simplified using various methods.
For example, can be by the failure and all column data phases with any other column in test correlation matrix model
Same column data is deleted.Referring to Fig. 3, the corresponding column data of test point T2 and T3 in Fig. 3 is identical, can by test point T2 and
The corresponding column data of any test point is deleted in T3.It preferably, can be according to wind-power electricity generation in the column data that selection is deleted
The product design situation of unit deletes test relatively difficult to achieve and the corresponding column data of the higher test point of testing expense
It removes.
For example, can be by the failure and all row data phases with any other a line in test correlation matrix model
Same row data, merge with the row data of described any other a line.Reference Fig. 3,
The corresponding row data of source of trouble F2 and F3 in Fig. 3 are identical, can by the corresponding row data of the source of trouble F2 and F3 into
Row merges.
When carrying out above-mentioned simplified, elastic processing can be carried out according to the specific requirement of fault diagnosis.Such as to product
In the case that fuzziness can be more than or equal to 2 in testbility demand, to failure and test correlation matrix model simplification
When, in there are two rows or the corresponding element of multirow row matrix when only one element difference, it is corresponding that the element can be deleted
Test point, and these identical rows are merged.
In step S40, the event of the function system to be diagnosed is determined according to the failure and test correlation matrix model
Hinder detection test point.It further include to the event in the method for diagnosing faults of the wind power generating set of embodiment according to the present invention
In the case that barrier carries out simplified step with test correlation matrix model, in step S40, according to simplified failure and test
Correlation matrix model determines the fault detection test point of the function system to be diagnosed.
The fault detection test point refers to the test that can detect that function system to be diagnosed breaks down in test point
Point.Here, various methods can be used to determine the function series to be diagnosed according to the failure and test correlation matrix model
The fault detection test point of system.
For example, fault detection test point can be determined by executing the step in the flow chart shown in Fig. 4.
Fig. 4 shows the flow chart of the step of determination fault detection test point of embodiment according to the present invention.
Referring to Fig. 4, in step S401, by matrix (the i.e. above-mentioned cloth in the failure and test correlation matrix model
That matrix) it is used as fault detection weight matrix.
In step S402, the fault detection weight of each test point is determined according to the fault detection weight matrix.
Here, various methods can be used to determine the fault detection of each test point according to the fault detection weight matrix
Weight.For example, the fault detection weight of any test point can be determined in the following manner: will be in the fault detection weight matrix
The value of all elements in column corresponding to any test point is added to obtain the fault detection weight of any test point.
In step S403, the fault detection that the test point of fault detection maximum weight is determined as this determination is tested
Point.That is, the test point of the fault detection maximum weight in step S402 to be determined as to the fault detection of this determination
Use test point.
In step S404, the fault detection test point and the fault detection weight matrix determined according to this is obtained
First submatrix, wherein first submatrix is by the fault detection weight matrix, this fault detection determined is surveyed
Row composition where the element that the corresponding column mean of pilot is 0.
In step S405, judge in the fault detection weight matrix, this fault detection determined is corresponding with test point
Column in the presence or absence of numerical value be 0 element.If it is present using first submatrix as the fault detection weight square
Battle array simultaneously recycles execution step S401 to step S405；If it does not exist, then terminating the process of determining fault detection test point.
In this way, first submatrix as the fault detection weight matrix and is recycled execution step S401 to step
S405, until in the fault detection weight matrix, there is no numbers in this corresponding column of fault detection test point determined
Until the element that value is 0.
Referring again to Fig. 1, in step S50, the test signal of the fault detection test point is detected, and according to detecting
Test signal determine the failure of function system to be diagnosed.That is, according to the test signal of fault detection test point come
Determine whether function system to be diagnosed breaks down.Here, monitoring component packet undetermined corresponding for fault detection test point
The case where including mechanical part, it is settable for checking the sensor of the state of the mechanical part, by the survey for detecting the sensor
Trial signal detects the test signal of the corresponding fault detection test point of the mechanical part.
Particularly, when the test signal of at least one of the fault detection test point is abnormal, determine to
Diagnostic function system jam.When the test signal of the fault detection test point is all normal, determine to diagnostic function
There is no failures for system.
When determination is broken down wait diagnose function system, it can prompt function system to be diagnosed that event occurs to staff
Barrier；Can also direction wind-driven generator group master control system transmission indicate the information that function system to be diagnosed breaks down, by master control system
It unites and prompts function system to be diagnosed to break down to staff；To which staff can check the failure.
In addition, the method for diagnosing faults of the wind power generating set of embodiment according to the present invention can also be to having broken down
The failure of function system is positioned.The method for diagnosing faults may also include (not shown): related to test according to the failure
Property matrix model determine the Fault Isolation test point of the function system to be diagnosed；When the function system to be diagnosed has event
When barrier, detect the test signal of the Fault Isolation test point, according to the test signal of Fault Isolation test point come
Trouble unit is determined in monitoring component undetermined.It here, can be according to the test signals of multiple Fault Isolation test points whether just
Normal assembled state, to infer corresponding trouble unit, for example, when diagnosing function system is train, when all events
Phragma from it is all abnormal with the test signal of test point when, then can determine that its trouble unit is first Fault Isolation test point pair
The component to be monitored answered.Here, monitoring component undetermined corresponding for Fault Isolation test point includes the case where mechanical part,
The sensor of the settable state for being used to check the mechanical part, detects the machinery by detecting the test signal of the sensor
The test signal of the corresponding Fault Isolation test point of component.
The Fault Isolation test point refers to that can test signal determination in test point according to it leads to function series to be diagnosed
The test point for the component that system breaks down.Here, various methods can be used to come according to the failure and test correlation matrix mould
Type determines the Fault Isolation test point of the function system to be diagnosed.
For example, Fault Isolation test point can be determined by executing the step in the flow chart shown in Fig. 5.
Fig. 5 shows the flow chart of the step of determination Fault Isolation test point of embodiment according to the present invention.
It uses test point as fixed Fault Isolation test point in step S501 referring to Fig. 5 fault detection, presses
Determine that sequence divides the matrix in the failure and test correlation matrix model according to each fault detection test point
It cuts to obtain Fault Isolation weight matrix.Particularly, according to first determining fault detection test point to the failure with
Matrix in test correlation matrix model is split to obtain two submatrixs, is surveyed according to the fault detection of next determination
The submatrix that pilot obtains last segmentation is split, and will be divided obtained submatrix for the last time and is weighed as Fault Isolation
Value matrix.In each segmentation, according to following partitioning scheme, by each divided Factorization algorithm, for two submatrixs, (second is sub
Matrix and third submatrix): the second submatrix is by the Fault Isolation test point pair in divided matrix, for subdivision matrix
Row composition where the element that the column mean answered is 0, third submatrix is by the failure in divided matrix, for subdivision matrix
Row composition where the element that isolation is 1 with the corresponding column mean of test point.
In step S502, the Fault Isolation weight of each test point is determined according to Fault Isolation weight matrix.It below will be detailed
Thin description determines the concrete mode of the Fault Isolation weight of each test point according to Fault Isolation weight matrix.
In step S503, the Fault Isolation that the test point of Fault Isolation maximum weight is determined as this determination is tested
Point.
In step S504, according to the partitioning scheme in step S501, the Fault Isolation test point determined according to this is incited somebody to action
Each Fault Isolation weight matrix is divided into two submatrixs respectively.
In step S505, judge whether each Fault Isolation weight matrix only remains data line.If it is not, then will step
The submatrix divided in rapid S504 is as Fault Isolation weight matrix and recycles execution step S502 to step S505；If
It is the process for then terminating to determine Fault Isolation test point.
In this way, the submatrix divided in step S504 as Fault Isolation weight matrix and is recycled execution step
S502 to step S505, until each Fault Isolation weight matrix only remains data line.
Here, determining Fault Isolation test point includes fixed Fault Isolation test point and every in step S501
Secondary circulation executes the Fault Isolation test point that step S502 is determined into step S505.
Here, various methods can be used determined according to the Fault Isolation weight matrix each test point failure inspection every
From weight.For example, the Fault Isolation weight of any test point can be determined in the following manner: calculating each Fault Isolation weight square
First product of battle array, wherein the first product of each Fault Isolation weight matrix is the institute in each Fault Isolation weight matrix
State the quantity for the element that column mean corresponding to any test point is 0 and the product of the quantity of element that value is 1；Institute is faulty
First product of isolation weight matrix is added, and the Fault Isolation weight of any test point is obtained.
Fig. 6 is the block diagram for showing the failure diagnosis apparatus of wind power generating set of embodiment according to the present invention.Shown in Fig. 6
Failure diagnosis apparatus be applicable to diagnosis wind power generating set function system whether break down.The wind power generating set
Including multiple function systems, such as: yaw system, pitch-controlled system and converter system etc..Each function in wind power generating set
Energy system includes component relevant to the function of the function system is realized.Referring to Fig. 6, the wind-force of embodiment according to the present invention is sent out
The failure diagnosis apparatus of motor group includes that system structure determines that program module 10, element determine program module 20, model foundation journey
Sequence module 30, detection determine program module 40 and detection program module 50 with test point.
System structure determines that program module 10 determines the system structure of the function system to be diagnosed of wind power generating set.It is described
Function system to be diagnosed refers to wait diagnose the function system whether to break down.The system structure of the function system to be diagnosed is
Refer to the system structure of relevant to the function of function system to be diagnosed is realized component composition, which includes mechanical part and electrical
Element.
Element determines that program module 20 determines monitoring component undetermined in the component of the system structure.The monitoring undetermined
Component, which refers to, may cause the component that function system to be diagnosed breaks down.It is appreciated that for the electrical of multiple contacts
Component, for example, contactor may include that main contacts and auxiliary contact can will take part in the system in an embodiment of the present invention
Each contact of the electrical control of structure is considered as a component.
Here, whole part or part components in the component of the system structure can be determined as monitoring component undetermined.
For example, whole components in the component of the system structure can be determined as monitoring portion undetermined when system structure is relatively simple
Part.It, can be according to various failure analysis methods by the portion in the component of the system structure when the system structure is complex
Sub-unit is determined as monitoring component undetermined, to reduce the calculation amount of remaining processing sequences module.
Preferably, element determines that program module 20 is come in the component of the system structure really in combination with Fault Tree Analysis
Fixed monitoring component undetermined.Specifically, in the component of the system structure, according to the system structure to described to diagnostic function
System carries out failure tree analysis (FTA) to be determined to the failure associated components for causing the function system to be diagnosed to break down；Institute
It states and determines monitoring component undetermined in failure associated components.
Here, whole part or part components in the failure associated components can be determined as monitoring component undetermined.Example
Such as, when system structure is relatively simple, whole components in the failure associated components can be determined as monitoring component undetermined.?
When the system structure is complex, the section components in the failure associated components can be determined according to various analysis methods
For monitoring component undetermined, to reduce the calculation amount of remaining processing sequences module.
Preferably, element determines that program module 20 can be in the following manner by the portions in the failure associated components
Part is determined as monitoring component undetermined: obtaining the historical failure data of the function system to be diagnosed；According to the historical failure number
According to the failure proportion of each failure associated components of determination, wherein the failure proportion of each failure associated components is served as reasons
The historical failure number of the function system to be diagnosed caused by each failure associated components and historical failure total degree
Ratio；Failure proportion in the failure associated components is greater than the failure associated components of predetermined value as monitoring portion undetermined
Part.
Model-builder program module 30 is according to the directions of information flow between monitoring component undetermined each in the system structure
Establish failure and test correlation matrix model.
Here, the system first can be established according to the directions of information flow between monitoring component undetermined each in the system structure
The information flow model for structure of uniting establishes failure and test correlation matrix model further according to the information flow model.The information flow
Model embodies the directions of information flow between each monitoring component undetermined.Fig. 2 shows the information of embodiment according to the present invention
The example of flow model.As shown in Fig. 2, the symbol (such as F1, F2, F3 and F4) in box indicates that monitoring component undetermined, arrow indicate
Directions of information flow.
The failure and test correlation matrix model refer to that the correlation logic between faults source and test point closes
The Boolean matrix of system.Particularly, in the Boolean matrix, all elements are logical value (such as 0 or 1).In the Boolean matrix
In, row corresponds to the source of trouble, and column correspond to test point.The element representation element in the Boolean matrix is expert at corresponding failure
When source is broken down, whether the corresponding test point of column where the element can test the fault message of the source of trouble.The element
Indicate that the test point cannot test the fault message of the source of trouble when being 0, which indicates that the test point can test when being 1
The fault message of the source of trouble.
In an embodiment of the present invention, the failure and test correlation matrix model the source of trouble include it is described it is each to
Determine monitoring component, the failure is with the test point in test correlation matrix model for testing and each monitoring component phase undetermined
The output signal of pass.Output signal relevant to each monitoring component undetermined, which refers to, can embody whether each monitoring component undetermined is sent out
The signal of raw failure.The case where being electrical component for monitoring component undetermined, which refers to the defeated of electrical component itself
Signal out；The case where being mechanical part for monitoring component undetermined, which refers to the shape for detecting the mechanical part
The output signal of the sensor of state.
Fig. 3 shows the failure that information flow model shown in Fig. 2 according to the present invention is established and test correlation matrix model.
As shown in Figures 2 and 3, T1, T2, T3 and T4 indicate each test point, each source of trouble of element representation in Boolean matrix shown in Fig. 3
Whether the fault message of F1, F2, F3 and F4 can be tested in each test point T1, T2, T3 and T4 is arrived.
After establishing the failure and test correlation matrix model, in order to reduce the calculating of remaining processing sequences module
Amount, the failure diagnosis apparatus may also include simplified program module (not shown).The simplified program module uses various methods
The failure and test correlation matrix model are simplified.
For example, can be by the failure and all column data phases with any other column in test correlation matrix model
Same column data is deleted.Referring to Fig. 3, the corresponding column data of test point T2 and T3 in Fig. 3 is identical, can by test point T2 and
The corresponding column data of any test point is deleted in T3.It preferably, can be according to wind-power electricity generation in the column data that selection is deleted
The product design situation of unit deletes test relatively difficult to achieve and the corresponding column data of the higher test point of testing expense
It removes.
For example, can be by the failure and all row data phases with any other a line in test correlation matrix model
Same row data, merge with the row data of described any other a line.Referring to Fig. 3, the source of trouble F2 and F3 in Fig. 3 are corresponding
Row data it is identical, can be by the corresponding row data of the source of trouble F2 and F3 to merging.
When carrying out above-mentioned simplified, elastic processing can be carried out according to the specific requirement of fault diagnosis.For example, to product
Testbility demand in fuzziness can be in the case where more than or equal to 2, to failure and test correlation matrix model letter
When change, in there are two rows or the corresponding element of multirow row matrix when only one element difference, it is corresponding that the element can be deleted
Test point, and these identical rows are merged.Detection determines program module 40 according to the failure with test point and surveys
Try the fault detection test point that correlation matrix model determines the function system to be diagnosed.In embodiment according to the present invention
The failure diagnosis apparatus of wind power generating set further include that simplified letter is carried out to the failure and test correlation matrix model
In the case where changing program module, detection determines program module 40 according to simplified failure and test correlation matrix with test point
Model determines the fault detection test point of the function system to be diagnosed.
The fault detection test point refers to the test that can detect that function system to be diagnosed breaks down in test point
Point.Here, various methods can be used to determine the function series to be diagnosed according to the failure and test correlation matrix model
The fault detection test point of system.For example, can determine that fault detection is surveyed by executing the step in the flow chart shown in Fig. 4
Pilot.
Detection program module 50 detects the test signal of the fault detection test point, and is believed according to the test detected
Number determine the failure of function system to be diagnosed.That is, determining follow-up according to the test signal of fault detection test point
Whether disconnected function system breaks down.Here, monitoring component undetermined corresponding for fault detection test point includes Machinery Ministry
The case where part, it is settable for check the mechanical part state sensor, by detect the test signal of the sensor come
Detect the test signal of the corresponding fault detection test point of the mechanical part.
Particularly, when the test signal of at least one of the fault detection test point is abnormal, determine to
Diagnostic function system jam.When the test signal of the fault detection test point is all normal, determine to diagnostic function
There is no failures for system.
When determination is broken down wait diagnose function system, it can prompt function system to be diagnosed that event occurs to staff
Barrier；Can also direction wind-driven generator group master control system transmission indicate the information that function system to be diagnosed breaks down, by master control system
It unites and prompts function system to be diagnosed to break down to staff；To which staff can check the failure.
In addition, the failure diagnosis apparatus of the wind power generating set of embodiment according to the present invention can also be to having broken down
The failure of function system is positioned.The failure diagnosis apparatus may also include isolation and determine that program module (is not shown with test point
Out).Isolation determines that program module determines the function to be diagnosed according to the failure and test correlation matrix model with test point
The Fault Isolation test point of energy system.When described wait diagnose function system there are when failure, detection program module 50 detects institute
The test signal for stating Fault Isolation test point, according to the test signal of Fault Isolation test point come in monitoring portion undetermined
Trouble unit is determined in part.Here, can according to the whether normal assembled state of test signal of multiple Fault Isolation test points,
Corresponding trouble unit is inferred, for example, when diagnosing function system is train, when all Fault Isolation test points
Test signal it is all abnormal when, then can determine that its trouble unit is the corresponding portion to be monitored of first Fault Isolation test point
Part.Here, monitoring component undetermined corresponding for Fault Isolation test point includes the case where mechanical part, settable for examining
The sensor for looking into the state of the mechanical part detects the corresponding event of the mechanical part by detecting the test signal of the sensor
Phragma is from the test signal with test point.
The Fault Isolation test point refers to that can test signal determination in test point according to it leads to function series to be diagnosed
The test point for the specific component that system breaks down.Here, various methods can be used to come according to the failure and test correlation square
Battle array model determines the Fault Isolation test point of the function system to be diagnosed.For example, can be by executing the flow chart shown in Fig. 5
In step determine Fault Isolation test point.
The method for diagnosing faults and equipment of the wind power generating set of embodiment according to the present invention, can be according to failure and test
Correlation matrix model determines fault detection test point, so as to pass through the test signal of detection fault detection test point
Quickly to determine the failure of function system to be diagnosed.
In addition, the method for diagnosing faults and equipment of the wind power generating set of embodiment according to the present invention, it can be according to failure
Fault Isolation test point is determined with test correlation matrix model, so as to pass through the survey of detection Fault Isolation test point
Trial signal is quickly positioned to treat the failure that diagnostic function system has occurred.
The embodiment of the present invention also provides a kind of computer readable storage medium, which has
Computer program, the computer program are configured as that the processor of computer is made to execute above-mentioned method for diagnosing faults.
The embodiment of the present invention also provides a kind of including above-mentioned computer readable storage medium computer.
Moreover, it should be understood that above-mentioned computer readable recording medium is can to store the data read by computer system
Arbitrary data storage device.The example of computer readable recording medium includes: read-only memory, random access memory, read-only
CD, tape, floppy disk, optical data storage devices and the carrier wave (data for such as passing through internet through wired or wireless transmission path
Transmission).Computer readable recording medium also can be distributed in the computer system of connection network, so that computer-readable code is to divide
Cloth stores and executes.It can be easily related to the present invention in addition, completing function program, code and code segment of the invention
The ordinary programmers in field explain within the scope of the present invention.
In addition, in the failure diagnosis apparatus of the wind power generating set of the embodiment of an exemplary embodiment of the present invention
Each program module can be realized by hardware completely, such as field programmable gate array or specific integrated circuit；It can also be by hard
Mode that part and software combine is realized；It can also be realized completely by computer program with software mode.
Although being particularly shown and describing the present invention, those skilled in the art referring to its exemplary embodiment
It should be understood that in the case where not departing from the spirit and scope of the present invention defined by claim form can be carried out to it
With the various changes in details.
Claims (18)
1. a kind of method for diagnosing faults of wind power generating set characterized by comprising
Determine the system structure of the function system to be diagnosed of wind power generating set；
Monitoring component undetermined is determined in the component of the system structure；
Failure and test correlation square are established according to the directions of information flow between monitoring component undetermined each in the system structure
Battle array model；
The fault detection test point of the function system to be diagnosed is determined according to the failure and test correlation matrix model；
The test signal of the fault detection test point is detected, and function series to be diagnosed are determined according to the test signal detected
The failure of system.
2. method for diagnosing faults according to claim 1, which is characterized in that the failure and test correlation matrix model
The source of trouble include each monitoring component undetermined, the failure is with the test point in test correlation matrix model for surveying
Examination output signal relevant to each monitoring component undetermined.
3. method for diagnosing faults according to claim 1, which is characterized in that according to the test signal that detects determine to
In the step of failure of diagnostic function system, when the test signal of at least one of the fault detection test point is abnormal
When, determine that function system to be diagnosed breaks down.
4. method for diagnosing faults according to claim 1, which is characterized in that further include:
The Fault Isolation test point of the function system to be diagnosed is determined according to the failure and test correlation matrix model；
Wait diagnose function system, there are the test signals for when failure, detecting the Fault Isolation test point when described, according to institute
The test signal of Fault Isolation test point is stated to determine trouble unit in monitoring component undetermined.
5. method for diagnosing faults according to claim 1, which is characterized in that in the component of the system structure determine to
The step of determining monitoring component include:
In the component of the system structure, failure is carried out to the function system to be diagnosed according to the structure of the system structure
Tree analysis is to be determined to cause the failure associated components that the function system to be diagnosed breaks down；
Monitoring component undetermined is determined in the failure associated components.
6. method for diagnosing faults according to claim 1, which is characterized in that determination is undetermined in the failure associated components
Monitoring component step includes:
Obtain the historical failure data of the function system to be diagnosed；
The failure proportion of each failure associated components is determined according to the historical failure data, wherein each failure is related
The failure proportion of component be as caused by each failure associated components described in function system to be diagnosed historical failure
The ratio of number and historical failure total degree；
Failure proportion in the failure associated components is greater than the failure associated components of predetermined value as monitoring portion undetermined
Part.
7. method for diagnosing faults according to claim 1, which is characterized in that in the event for determining the function system to be diagnosed
Before barrier detection test point further include:
Simplify the failure and test correlation matrix model.
8. method for diagnosing faults according to claim 7, which is characterized in that simplify the failure and test correlation matrix
The step of model includes:
By the failure and all column datas identical with the column data of any other column in test correlation matrix model
It is deleted；And/or
By the failure and all row data identical with the row data of any other a line in correlation matrix model are tested,
It is merged with the row data of described any other a line.
9. a kind of failure diagnosis apparatus of wind power generating set characterized by comprising
System structure determines program module, determines the system structure of the function system to be diagnosed of wind power generating set；
Element determines program module, and monitoring component undetermined is determined in the component of the system structure；
Model-builder program module establishes event according to the directions of information flow between monitoring component undetermined each in the system structure
Barrier and test correlation matrix model；
Detection determines program module with test point, determines the function to be diagnosed according to the failure and test correlation matrix model
The fault detection test point of energy system；
Program module is detected, detects the test signal of the fault detection test point, and true according to the test signal detected
The failure of fixed function system to be diagnosed.
10. failure diagnosis apparatus according to claim 9, which is characterized in that the failure and test correlation matrix mould
The source of trouble of type includes each monitoring component undetermined, and the failure is used for the test point in test correlation matrix model
Test output signal relevant to each monitoring component undetermined.
11. failure diagnosis apparatus according to claim 9, which is characterized in that when in the fault detection test point
When the test signal of at least one is abnormal, detection program module determines that function system to be diagnosed breaks down.
12. failure diagnosis apparatus according to claim 9, which is characterized in that further include: isolation determines program with test point
Module determines that the Fault Isolation of the function system to be diagnosed is tested according to the failure and test correlation matrix model
Point；
When described wait diagnose function system there are when failure, detection program module detects the test of the Fault Isolation test point
Signal determines trouble unit according to the test signal of Fault Isolation test point in monitoring component undetermined.
13. failure diagnosis apparatus according to claim 9, which is characterized in that element determines program module in the system
In the component of structure, failure tree analysis (FTA) is carried out to the function system to be diagnosed to be determined to cause according to the system structure
The failure associated components that the function system to be diagnosed breaks down,
Monitoring component undetermined is determined in the failure associated components.
14. failure diagnosis apparatus according to claim 9, which is characterized in that element determine program module obtain it is described to
The historical failure data of diagnostic function system determines that the failure of each failure associated components occurs according to the historical failure data
Ratio, wherein the failure proportion of each failure associated components be as caused by each failure associated components described in
The historical failure number of diagnostic function system and the ratio of historical failure total degree,
Failure proportion in the failure associated components is greater than the failure associated components of predetermined value as monitoring portion undetermined
Part.
15. failure diagnosis apparatus according to claim 9, which is characterized in that further include simplifying program module, in determination
Before the fault detection test point of the function system to be diagnosed, simplify the failure and test correlation matrix model.
16. failure diagnosis apparatus according to claim 15, which is characterized in that simplify program module for the failure and survey
All column datas identical with the column data of any other column in examination correlation matrix model are deleted；And/or
By the failure and all row data identical with the row data of any other a line in correlation matrix model are tested,
It is merged with the row data of described any other a line.
17. a kind of computer readable storage medium, is stored with computer program, which is characterized in that the computer program is matched
Being set to makes the processor of computer execute method for diagnosing faults as described in any of the claims 1 to 8.
18. a kind of computer, which is characterized in that including computer readable storage medium as claimed in claim 17.
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Application publication date: 20181207 |