CN115169038B - FMECA-based reliability analysis method and device for offshore floating fan - Google Patents
FMECA-based reliability analysis method and device for offshore floating fan Download PDFInfo
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Abstract
The application provides a method and a device for analyzing reliability of an offshore floating fan based on FMECA, wherein the method comprises the following steps: decomposing the offshore floating fan into a preset number of systems according to the executed functions, and determining equipment or subsystems to be analyzed in each system; acquiring fault modes of the offshore floating fans and each system, and analyzing fault reasons and fault influences of the fault modes; taking the system, the equipment or the subsystem as a fault unit, analyzing the hazard degree of the fault mode based on three indexes of severity, incidence and detection degree, and judging the risk level of the fault unit; and determining the operation strategy and maintenance measures of the offshore floating fan in an auxiliary manner according to the reliability analysis result. The method carries out comprehensive, systematic and highly reliable reliability analysis on the offshore floating fan, and is beneficial to ensuring the systematic reliability of the offshore floating fan.
Description
Technical Field
The application relates to the technical field of wind power generation, in particular to an offshore floating fan reliability analysis method and device based on FMECA.
Background
With the development of wind power generation technology, in order to fully utilize abundant offshore wind energy, modern wind energy industry is gradually gathering from onshore wind power to offshore wind power, and offshore wind turbines are also being lifted from offshore stationary floating wind turbines, and the popularity of the offshore floating wind turbines is gradually increasing.
However, factors such as the large-scale fan, the extreme marine environment and the lack of design and operation and maintenance experience bring a plurality of difficulties to the development and construction of the offshore floating fan, and mainly comprise the following points: firstly, the offshore wind power has high cost, and economic advantages are not completely revealed; secondly, the failure rate of the offshore floating fan is far higher than that of the land fan; and thirdly, the operation and maintenance cost is high, the operation and maintenance cost of the mature land-based fan and the offshore fixed foundation fan accounts for 20% -30% of the total economic benefit of the land-based fan and the offshore floating fan is expected to exceed 35%. Thus, the development prospect and economic advantage of the offshore floating wind turbines require higher system reliability, and the reliability analysis of the offshore floating wind turbines is the basis for the reliability, safety, availability, maintenance and economic study thereof, so that the reliability analysis of the offshore floating wind turbines is necessary. However, in the reliability analysis scheme of the offshore floating fan in the related art, the reliability of an analysis result is low and an analysis process is one-sided.
Disclosure of Invention
The present application aims to solve, at least to some extent, one of the technical problems in the related art.
Therefore, a first object of the present application is to provide a reliability analysis method for an offshore floating fan based on FMECA, which is based on FMECA analysis, and performs comprehensive, systematic and highly reliable reliability analysis on the offshore floating fan from two aspects of qualitative analysis and quantitative analysis, thereby being beneficial to ensuring the system reliability of the offshore floating fan.
A second object of the present application is to propose an offshore floating wind turbine reliability analysis device based on FMECA;
a third object of the present application is to propose a non-transitory computer readable storage medium.
To achieve the above object, an embodiment of a first aspect of the present application provides a method for analyzing reliability of an offshore floating fan based on FMECA, the method comprising the steps of:
decomposing the offshore floating fan into a preset number of systems according to the executed functions, and determining equipment or subsystems to be analyzed, which are included in each system;
acquiring fault modes of the offshore floating fans and each system, and analyzing fault reasons and fault influences of the fault modes to realize qualitative analysis of reliability;
taking the system, the equipment or the subsystem as a fault unit, performing hazard degree analysis on the fault mode based on three indexes of severity, occurrence degree and detection degree, and judging the risk level of the fault unit so as to realize reliability quantitative analysis;
and determining the operation strategy and maintenance measures of the offshore floating fan in an auxiliary manner according to the reliability analysis result.
Optionally, in one embodiment of the present application, the predetermined number of systems into which the offshore floating wind turbine is decomposed includes: wind energy receiving system, electrical energy production system, electrical energy conversion system, support structure system and auxiliary system, said determining each of said systems comprising a device or subsystem to be analyzed comprising: decomposing the wind energy receiving system into blades and a hub; decomposing the electric energy production system into a main shaft, a main bearing, a gear box and a generator; decomposing the electric energy conversion system into a rectifier and a transformer; decomposing the support structure system into a tower, a tower and a mooring subsystem; the auxiliary system is broken down into a yaw subsystem, a pitch subsystem, a controller, and an electronics subsystem.
Optionally, in one embodiment of the present application, performing hazard analysis on each of the fault modes based on three indexes of severity, occurrence and detection degree and evaluating a risk level of the fault unit includes: formulating quantization criteria for said severity, said occurrence and said detection; calculating a risk priority number RPN of the fault unit according to the quantization criterion; and ordering all the risk priority numbers RPNs in the order from the top to the bottom.
Optionally, in one embodiment of the present application, the risk priority RPN is calculated by the following formula:
RPN＝S×O×D
where S is severity, O is occurrence, and D is detection.
Optionally, in one embodiment of the present application, after said analyzing the fault cause and the fault influence of the fault mode, it includes: establishing fault avoidance measures according to the fault reasons and analysis results of the fault influence; after said sorting all of said risk priority RPNs in order from big to small, further comprising: determining a target fault unit with a risk level above a preset risk level threshold according to the sequencing result; and taking the corresponding fault avoidance measures aiming at the target fault unit.
To achieve the above object, an embodiment of the second aspect of the present application further provides an offshore floating fan reliability analysis device based on FMECA, including the following modules:
the decomposing module is used for decomposing the offshore floating fan into a preset number of systems according to the executed functions and determining equipment or subsystems to be analyzed, wherein each system comprises;
the first analysis module is used for acquiring fault modes of the offshore floating fans and each system and analyzing fault reasons and fault influences of the fault modes so as to realize qualitative analysis of reliability;
the second analysis module is used for taking the system, the equipment or the subsystem as a fault unit, carrying out hazard degree analysis on the fault mode based on three indexes of severity, occurrence degree and detection degree, and judging the risk level of the fault unit so as to realize reliability quantitative analysis;
and the determining module is used for assisting in determining the operation strategy and maintenance measures of the offshore floating fan according to the reliability analysis result.
Optionally, in one embodiment of the present application, the predetermined number of systems into which the offshore floating wind turbine is decomposed includes: wind energy receiving system, electric energy production system, electric energy conversion system, bearing structure system and auxiliary system, decomposition module is specifically used for: determining that the wind energy receiving system comprises a blade and a hub; determining that the electrical energy production system comprises a main shaft, a main bearing, a gearbox and a generator; determining that the electrical energy conversion system includes a rectifier and a transformer; determining that the support structure system includes a tower, and a mooring subsystem; the auxiliary system is determined to include a yaw subsystem, a pitch subsystem, a controller, and an electronics subsystem.
Optionally, in one embodiment of the present application, the second analysis module is specifically configured to: formulating quantization criteria for said severity, said occurrence and said detection; calculating a risk priority number RPN of the fault unit according to the quantization criterion; and ordering all the risk priority numbers RPNs in the order from the top to the bottom.
Optionally, in one embodiment of the present application, the second analysis module is specifically configured to calculate the risk priority number RPN by the following formula:
RPN＝S×O×D
where S is severity, O is occurrence, and D is detection.
The technical scheme provided by the embodiment of the application at least brings the following beneficial effects: based on the FMECA analysis mode, comprehensive, systematic and high-reliability analysis is performed on the offshore floating fan from two aspects of qualitative analysis and quantitative analysis, and accuracy and reliability of the reliability analysis of the offshore floating fan are improved. And, the occurrence of faults is predicted by the method, the occurrence of faults is avoided by making fault avoidance measures, wherein, key fault units with high risk level are selected according to quantitative analysis results to take measures to avoid faults, and on the basis of reducing the probability of faults of the offshore floating fan, the taking of inefficient fault avoidance measures is avoided, so that the system reliability of the offshore floating fan can be ensured, and resources are prevented from being wasted.
In order to implement the above embodiment, an embodiment of the third aspect of the present application further proposes a non-transitory computer readable storage medium, on which a computer program is stored, which when executed by a processor implements the method for analyzing reliability of an offshore floating fan based on FMECA in the above embodiment.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:
FIG. 1 is a flow chart of an offshore floating fan reliability analysis method based on FMECA according to an embodiment of the present application;
FIG. 2 is a flow chart of a method for quantitative analysis of reliability of an offshore floating fan according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a specific severity, occurrence, and detectivity quantization criterion according to an embodiment of the present application;
FIG. 4 is a flowchart of a specific method for analyzing reliability of an offshore floating wind turbine based on FMECA according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an offshore floating fan reliability analysis system based on FMECA according to an embodiment of the present application.
Detailed Description
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative and intended to explain the present invention and should not be construed as limiting the invention.
The following describes in detail an offshore floating fan reliability analysis method and system based on FMECA according to the embodiments of the present application with reference to the accompanying drawings.
Fig. 1 is a flowchart of an offshore floating fan reliability analysis method based on FMECA according to an embodiment of the present application, as shown in fig. 1, the method includes the following steps:
step S101, decomposing the offshore floating fan into a preset number of systems according to the executed function, and determining equipment or subsystems to be analyzed, which are included in each system.
In this application, reliability analysis refers to a systematic flow of collecting, characterizing, organizing reliability information, and obtaining a trusted analysis result according to a scientific and reasonable modeling method. The method for learning the avoidance of the fault from the fault in the reliability analysis process aims to predict the occurrence of the fault by learning the essential characteristics of the fault and to formulate avoidance measures of the fault. The present application also performs reliability analysis based on Failure Mode, impact, and hazard analysis (FMECA).
The FMECA includes fault mode and impact analysis (Failure Mode and Effects Analysis, FMEA) and hazard analysis (Criticality Analysis, CA). The FMECA distributes fault risk evaluation indexes for basic fault units of the analyzed products or systems, wherein the fault risk evaluation indexes comprise subjective indexes such as severity S, incidence O and detection D, objective indexes such as fault probability and fault cost, and further establishes a risk priority (Risk Priority Number, called RPN for short) to comprehensively judge the risk level of the basic fault units. Thus, the present application first breaks down the offshore floating wind turbine into a plurality of systems and determines the equipment or subsystems to be analyzed that each system includes for subsequent determination of the faulty unit for analysis.
Specifically, products or systems are decomposed firstly, in the application, the products, namely the offshore floating fans, are decomposed into a plurality of systems according to the functions of the systems, then each system is decomposed, and equipment or subsystems to be analyzed, which are included in each system, are determined, wherein only important equipment or subsystems, which need to be subjected to reliability analysis, in the systems are determined.
In one embodiment of the present application, the preset number of decomposed systems may be determined according to various factors such as the characteristics of the current offshore floating wind turbine and the accuracy requirements of the reliability analysis. As one possible implementation manner, the offshore floating fan can be decomposed into five systems, which are respectively: the system comprises a wind energy receiving system, an electric energy production system, an electric energy conversion system, a supporting structure system and an auxiliary system, and equipment or a subsystem to be analyzed, which is included in each system, is determined.
In this embodiment, the wind energy receiving system: comprising blades and a hub, the function of which is to convert wind energy into mechanical energy. An electric energy production system: the electromagnetic induction type mechanical energy conversion device comprises a main shaft, a main bearing, a gear box and a generator, and is used for converting mechanical energy into unstable electric energy according to an electromagnetic induction principle. An electric energy conversion system: the power generation system comprises a rectifier and a transformer, and is used for converting unstable electric energy generated by a generator into electric energy which is stable and meets the requirements of a booster station. Support structure system: the offshore floating type wind turbine comprises a tower drum, a tower and a mooring system, and is used for stably supporting main functional components of the offshore floating type wind turbine. Auxiliary system: the electric energy generator comprises a yaw system, a pitch system, a controller and an electronic component subsystem, and the functions of the yaw system, the pitch system, the controller and the electronic component subsystem are to ensure the production efficiency of electric energy.
And S102, acquiring fault modes of the offshore floating fans and each system, and analyzing fault reasons and fault influences of the fault modes to realize qualitative analysis of reliability.
The fault mode refers to a fault expression form of the offshore floating fan or each system, for example, the power supply quantity of an electric energy production system is insufficient, a tower barrel and a tower frame are corroded, cracked or deformed, equipment is short-circuited, and the like. The failure effect refers to the effect of the failure mode on the safety, the realized functions and the like of the offshore floating fan.
Specifically, the method and the device perform qualitative analysis on faults, namely perform fault mode and influence analysis, and include collecting fault modes of products or decomposed systems, namely acquiring all possible fault modes of the offshore floating fan, and determining reasons of occurrence of each fault mode and influence on operation of the offshore floating fan according to analysis of the fault modes.
In one embodiment of the present application, failure modes of a product or system may be collected in a variety of ways. For example, future potential failure modes may be obtained that are determined based on design data when designing the various constituent units of the offshore floating wind turbine during the design process. Or, the running state of the offshore floating fan can be detected, the running data of the offshore floating fan can be stored, the historical fault data of the offshore floating fan can be recorded, and then the fault mode in the historical data is collected.
Further, when analyzing the cause and influence of the fault in this embodiment, as a possible implementation manner, relevant data of all aspects of the offshore floating fan may be collected in advance, where the collected data includes structural and functional relevant data, operation and maintenance data, historical operation and operation data, environmental data where the fan is located, and the like, and then the collected data is combined to perform mechanism analysis on equipment, systems, and the like of the offshore floating fan, and the cause, influence and maintenance measures corresponding to each fault mode of the offshore floating fan are arranged according to the mechanism analysis result, so as to construct a fault diagnosis knowledge base for the offshore floating fan. When the analysis is actually performed, the collected fault modes are input into a fault knowledge base to analyze the reasons and influences of the fault modes.
In the embodiment, when the fault influence is analyzed, the fault influence can be analyzed from three angles of equipment, a system and an offshore floating fan, so that the comprehensiveness of fault influence analysis is improved. For example, if a slight contact failure occurs in a component in the electronic component subsystem in the above embodiment, the analysis of the failure mode in the present application may reduce the operation efficiency, reduce the effect of the auxiliary system in which the subsystem is located on the production efficiency of auxiliary electric energy, and finally may not affect the offshore floating fan. Therefore, the method and the device perform fault influence analysis from three levels of final influence of local equipment, systems and products, further improve the comprehensiveness and systematicness of fault influence analysis, and are beneficial to fully guaranteeing the reliability of the offshore floating fan.
And step S103, taking the system, equipment or a subsystem as a fault unit, analyzing the hazard degree of the fault mode based on three indexes of severity, incidence and detection degree, and judging the risk level of the fault unit so as to realize reliability quantitative analysis.
Specifically, the present application performs a fault hazard analysis (CA), that is, analyzes each fault mode obtained in step S102 according to the severity, occurrence probability and comprehensive influence of detectability of the impact, and establishes a risk priority RPN to comprehensively evaluate the risk level of the basic fault unit, thereby more comprehensively evaluating the influence of various fault modes and implementing quantitative analysis on the fault.
In order to more clearly illustrate the specific implementation of the hazard analysis of the present application, an analysis method set forth in one embodiment of the present application is described below as an example. Fig. 2 is a flowchart of a method for quantitatively analyzing reliability of an offshore floating fan according to an embodiment of the present application, as shown in fig. 2, the method includes the following steps:
in step S201, quantization criteria for severity, occurrence, and detection degree are formulated.
Specifically, when the hazard degree analysis is performed, the hazard degree analysis is performed by decomposing the hazard degree analysis into three indexes of severity, occurrence degree and detection degree, wherein the severity (S) is the result of occurrence of a fault mode, the occurrence degree (O) is the possibility of occurrence of the fault mode, and the detection degree (D) is the difficulty of detection of the fault mode. The method and the device have the advantages that the quantization criteria of severity, incidence and detection degree are formulated firstly, and the index quantization value of each fault mode can be conveniently determined later and then quantization calculation is carried out.
As an example, the present application proposes FMECA severity, occurrence, and detection degree quantization criteria as shown in fig. 3, and as can be seen from fig. 3, quantization values classified into 10 levels in the criteria, and judgment conditions of severity, occurrence, and detection degree corresponding to each quantization value are specified explicitly.
In step S202, the risk priority RPN of the faulty unit is calculated according to the quantization criterion.
Wherein the risk priority number RPN is a numerical representation of the risk level of the faulty unit.
It should be noted that, because the present application collects the failure modes of each device and each system in the offshore floating fan, the present application may use the system and each device or subsystem in the system as a failure unit, and calculate the risk priority RPN of the failure that may occur in each failure unit for two-stage failure units, thereby quantifying and evaluating the risk level of each level of failure unit, and further improving the systematicness and comprehensiveness of the reliability analysis.
In particular, the severity, occurrence, and detection of each failure mode may be determined based on quantization criteria, e.g., expert knowledge and historical experience in the field may be combined to determine which of the quantization criteria of fig. 3 each corresponds to. After determining the quantized values of severity, occurrence and detection, the risk priority RPN is calculated by the following formula:
RPN＝S×O×D
where S is severity, O is occurrence, and D is detection. That is, after determining the severity, occurrence, and detection quantitative values of the failure mode, the three indices are multiplied to obtain the corresponding values of the failure cell risk level.
In step S203, all risk priority numbers RPN are sorted in order from the top to the bottom.
Specifically, all risk priority numbers RPN are ordered according to the order from big to small, so that the risk level of each fault unit can be displayed intuitively, and the target fault unit can be determined subsequently.
Thus, the present application is based on FMECA, which is further quantitatively analyzed after qualitative analysis, wherein severity (S), incidence (O), detection (D), RPN and RPN are ranked as quantitative indicators of FMECA. In the FMECA analysis, the present application can collect and calculate data according to the following table 1:
TABLE 1
And step S104, the operation strategy and maintenance measures of the offshore floating fan are determined in an auxiliary mode according to the reliability analysis result.
Specifically, according to the reliability analysis result, suggestions and measures of the offshore floating fan in the operation and maintenance process are provided, and the operation strategy and maintenance measures of the offshore floating fan are prepared by combining the suggestions and measures and the actual working requirements and the working conditions of the offshore floating fan so as to ensure the system reliability of the offshore floating fan. For example, the resource allocation is adjusted and more maintenance measures are performed for faulty units with higher risk levels.
In order to further guarantee the system reliability of the offshore floating fan, in one implementation of the method, key fault units with high risk levels can be selected to take measures to avoid faults, and faults are avoided. In specific implementation, as a possible implementation manner, after the fault cause and the fault influence of the fault mode are analyzed in step S102, a fault avoidance measure may be formulated according to the analysis results of the fault cause and the fault influence, where the fault avoidance measure is used for removing the fault cause in advance, so as to avoid an accident. In specific implementation, all feasible solutions for solving the fault can be read from the fault diagnosis knowledge base in the embodiment, and then fault avoidance measures corresponding to the fault mode are formulated by the preventive scheme in the solution.
Further, after the total risk priority RPN is sorted in order from the top, the method further includes: determining a target fault unit with a risk level above a preset risk level threshold according to the sequencing result; and taking corresponding fault avoidance measures aiming at the target fault unit. That is, after the risk priority RPN is ranked in order from large to small, a critical fault unit with a high risk level may be selected according to the ranking result, where the risk level threshold may be a predetermined RPN value, which is used to distinguish between a high risk level and a low risk level, and when the calculated RPN value of the fault unit is greater than the RPN value, it indicates that the risk level of the fault unit is high. And then, aiming at the screened key fault units, adopting fault avoidance measures corresponding to the key fault units to avoid fault occurrence.
In summary, according to the reliability analysis method for the offshore floating fan based on the FMECA, based on the FMECA analysis mode, comprehensive, systematic and highly reliable reliability analysis is performed on the offshore floating fan from two aspects of qualitative analysis and quantitative analysis, and accuracy and reliability of the reliability analysis of the offshore floating fan are improved. And, the occurrence of faults is predicted by the method, the occurrence of faults is avoided by making fault avoidance measures, wherein, key fault units with high risk level are selected according to quantitative analysis results to take measures to avoid faults, and on the basis of reducing the probability of faults of the offshore floating fan, the taking of inefficient fault avoidance measures is avoided, so that the system reliability of the offshore floating fan can be ensured, and resources are prevented from being wasted.
In order to more clearly describe the reliability analysis method of the offshore floating fan based on the FMECA in the embodiment of the present application, a detailed description will be given below of an embodiment of the method for performing the FMECA analysis on the reliability of the offshore floating fan. Fig. 4 is a flowchart of a specific reliability analysis method of an offshore floating fan based on FMECA according to an embodiment of the present application, as shown in fig. 4, the reliability analysis method of the embodiment includes the following steps:
step S401: the product or system is broken down. Specifically, the offshore floating fan is decomposed into five systems.
Step S402: product or system failure modes are collected.
Step S403: and analyzing the fault reasons and fault influences.
Step S404: and (5) making fault avoidance measures.
The above steps S401 to S404 are qualitative analysis.
Step S405: and (5) carrying out hazard analysis, and decomposing the hazard analysis into three indexes of severity, incidence and detection degree.
Step S406: severity, occurrence, and detection quantification criteria are formulated.
Step S407: and calculating the RPN value and sequencing. Specifically, the risk priority RPN of the components and systems is calculated and sorted from large to small.
Step S408: operational and maintenance recommendations and measures are presented.
The above steps S405 to S408 are quantitative analysis.
It should be noted that, the specific implementation manner of each step in this embodiment may refer to the related description in the foregoing embodiment, which is not repeated herein.
In order to implement the above embodiment, the present application further provides an offshore floating fan reliability analysis device based on FMECA, and fig. 5 is a schematic structural diagram of the offshore floating fan reliability analysis device based on FMECA according to the embodiment of the present application, as shown in fig. 5, where the device includes a decomposition module 100, a first analysis module 200, a second analysis module 300, and a determination module 400.
The decomposing module 100 is configured to decompose the offshore floating fan into a preset number of systems according to the executed function, and determine a device or subsystem to be analyzed included in each system.
The first analysis module 200 is configured to obtain failure modes of the offshore floating fans and each system, and analyze failure causes and failure effects of the failure modes to realize qualitative analysis of reliability.
The second analysis module 300 is configured to take the system, the device or the subsystem as a fault unit, perform hazard analysis on the fault mode based on three indexes of severity, occurrence and detection degree, and judge the risk level of the fault unit, so as to implement reliability quantitative analysis.
The determining module 400 is used for assisting in determining the operation strategy and maintenance measures of the offshore floating fan according to the reliability analysis result.
Optionally, in one embodiment of the present application, the predetermined number of systems into which the offshore floating wind turbine is decomposed includes: wind energy receiving system, electrical energy production system, electrical energy conversion system, support structure system and auxiliary system, decomposition module 100, in particular for: determining that the wind energy receiving system comprises a blade and a hub; determining that the electric energy production system comprises a main shaft, a main bearing, a gear box and a generator; determining that the power conversion system comprises a rectifier and a transformer; determining that the support structure system includes a tower, and a mooring subsystem; the determination assistance system includes a yaw subsystem, a pitch subsystem, a controller, and an electronics subsystem.
Optionally, in one embodiment of the present application, the second analysis module 300 is specifically configured to: establishing a quantification criterion of severity, occurrence degree and detection degree; calculating the risk priority number RPN of the fault unit according to the quantization criterion; all risk priority RPNs are ordered in order of from big to small.
Optionally, in one embodiment of the present application, the second analysis module 300 is specifically configured to calculate the risk priority RPN by the following formula:
RPN＝S×O×D
where S is severity, O is occurrence, and D is detection.
Optionally, in an embodiment of the present application, the first analysis module 200 is further configured to formulate a fault avoidance measure according to the analysis results of the fault cause and the fault influence, and the determining module 400 is further configured to determine, according to the ranking result, a target fault unit with a risk level above a preset risk level threshold, and take a corresponding fault avoidance measure for the target fault unit.
It should be noted that the foregoing explanation of the embodiment of the FMECA-based method for analyzing reliability of the offshore floating fan is also applicable to the device of this embodiment, and will not be repeated herein.
In summary, according to the reliability analysis device for the offshore floating fan based on the FMECA provided by the embodiment of the application, the reliability analysis of the offshore floating fan with comprehensive, systematic and high reliability is performed on the basis of the two aspects of qualitative analysis and quantitative analysis based on the FMECA analysis mode, so that the accuracy and the reliability of the reliability analysis of the offshore floating fan are improved. And, the occurrence of faults is predicted by the method, the occurrence of faults is avoided by making fault avoidance measures, wherein, key fault units with high risk level are selected according to quantitative analysis results to take measures to avoid faults, and on the basis of reducing the probability of faults of the offshore floating fan, the taking of inefficient fault avoidance measures is avoided, so that the system reliability of the offshore floating fan can be ensured, and resources are prevented from being wasted.
In order to implement the above embodiments, the application further proposes a non-transitory computer readable storage medium, on which a computer program is stored, which when executed by a processor implements the FMECA-based offshore floating wind turbine reliability analysis method according to any of the above embodiments.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "plurality" is at least two, such as two, three, etc., unless explicitly defined otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and additional implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.
Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.
It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. As with the other embodiments, if implemented in hardware, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
Those of ordinary skill in the art will appreciate that all or a portion of the steps carried out in the method of the above-described embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, and where the program, when executed, includes one or a combination of the steps of the method embodiments.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing module, or each unit may exist alone physically, or two or more units may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules may also be stored in a computer readable storage medium if implemented in the form of software functional modules and sold or used as a stand-alone product.
The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, or the like. Although embodiments of the present application have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the application, and that variations, modifications, alternatives, and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the application.
Claims (3)
1. The method for analyzing the reliability of the offshore floating fan based on the FMECA is characterized by comprising the following steps of:
decomposing the offshore floating fan into a preset number of systems according to the executed functions, and determining equipment or subsystems to be analyzed, which are included in each system;
acquiring fault modes of the offshore floating fans and each system, and analyzing fault reasons and fault influences of the fault modes to realize qualitative analysis of reliability;
taking the system, the equipment or the subsystem as a fault unit, carrying out hazard degree analysis on the fault mode based on three indexes of severity, occurrence degree and detection degree, and judging the risk level of the fault unit to realize reliability quantitative analysis, wherein severity, occurrence degree, detection degree, RPN and RPN are sequenced as quantitative indexes;
and determining operation strategies and maintenance measures of the offshore floating fan in an auxiliary manner according to the reliability analysis result, wherein the operation strategies and maintenance measures comprise: according to the reliability analysis result, proposing the proposal and the measure of the offshore floating fan in the operation and maintenance process, combining the proposal and the measure, and the actual working requirement and the working condition of the offshore floating fan, and preparing the operation strategy and the maintenance measure of the offshore floating fan so as to ensure the system reliability of the offshore floating fan;
the hazard degree analysis is carried out on each fault mode based on three indexes of severity, occurrence degree and detection degree, and the risk level of the fault unit is judged, and the method comprises the following steps:
formulating quantization criteria for said severity, said occurrence and said detection;
calculating a risk priority number RPN of the fault unit according to the quantization criterion;
sorting all the risk priority numbers RPNs in order from big to small;
the risk priority RPN is calculated by the following formula:
RPN＝S×O×D
wherein S is severity, O is occurrence, and D is detection;
after said analyzing the fault cause and fault impact of said fault pattern, comprising:
establishing fault avoidance measures according to the fault reasons and analysis results of the fault influence;
after said sorting all of said risk priority RPNs in order from big to small, further comprising:
determining a target fault unit with a risk level above a preset risk level threshold according to the sequencing result;
taking the corresponding fault avoidance measures for the target fault unit;
the preset number of systems into which the offshore floating fan is decomposed comprises: wind energy receiving system, electrical energy production system, electrical energy conversion system, support structure system and auxiliary system, said determining each of said systems comprising a device or subsystem to be analyzed comprising:
determining that the wind energy receiving system comprises a blade and a hub;
determining that the electrical energy production system comprises a main shaft, a main bearing, a gearbox and a generator;
determining that the electrical energy conversion system includes a rectifier and a transformer;
determining that the support structure system includes a tower, and a mooring subsystem;
the auxiliary system is determined to include a yaw subsystem, a pitch subsystem, a controller, and an electronics subsystem.
2. The reliability analysis device of the offshore floating fan based on the FMECA is characterized by comprising the following modules:
the decomposing module is used for decomposing the offshore floating fan into a preset number of systems according to the executed functions and determining equipment or subsystems to be analyzed, wherein each system comprises;
the first analysis module is used for acquiring fault modes of the offshore floating fans and each system and analyzing fault reasons and fault influences of the fault modes so as to realize qualitative analysis of reliability;
the second analysis module is used for taking the system, the equipment or the subsystem as a fault unit, carrying out hazard degree analysis on the fault mode based on three indexes of severity, occurrence degree and detection degree, and judging the risk level of the fault unit so as to realize reliability quantitative analysis, wherein the severity, the occurrence degree, the detection degree, RPN and RPN are ordered as quantitative indexes;
the determining module is used for assisting in determining the operation strategy and maintenance measures of the offshore floating fan according to the reliability analysis result, and comprises the following steps: according to the reliability analysis result, proposing the proposal and the measure of the offshore floating fan in the operation and maintenance process, combining the proposal and the measure, and the actual working requirement and the working condition of the offshore floating fan, and preparing the operation strategy and the maintenance measure of the offshore floating fan so as to ensure the system reliability of the offshore floating fan;
the second analysis module is specifically configured to:
formulating quantization criteria for said severity, said occurrence and said detection;
calculating a risk priority number RPN of the fault unit according to the quantization criterion;
sorting all the risk priority numbers RPNs in order from big to small;
the second analysis module is specifically configured to calculate the risk priority RPN according to the following formula:
RPN＝S×O×D
wherein S is severity, O is occurrence, and D is detection;
the determining module is further configured to:
establishing fault avoidance measures according to the fault reasons and analysis results of the fault influence;
after said sorting all of said risk priority RPNs in order from big to small, further comprising:
determining a target fault unit with a risk level above a preset risk level threshold according to the sequencing result;
taking the corresponding fault avoidance measures for the target fault unit; the preset number of systems into which the offshore floating fan is decomposed comprises: wind energy receiving system, electric energy production system, electric energy conversion system, bearing structure system and auxiliary system, decomposition module is specifically used for:
determining that the wind energy receiving system comprises a blade and a hub;
determining that the electrical energy production system comprises a main shaft, a main bearing, a gearbox and a generator;
determining that the electrical energy conversion system includes a rectifier and a transformer;
determining that the support structure system includes a tower, and a mooring subsystem;
the auxiliary system is determined to include a yaw subsystem, a pitch subsystem, a controller, and an electronics subsystem.
3. A non-transitory computer readable storage medium having stored thereon a computer program which when executed by a processor implements the FMECA based offshore floating wind turbine reliability analysis method of claim 1.
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| CN202210789641.4A CN115169038B (en) | 2022-07-06 | 2022-07-06 | FMECA-based reliability analysis method and device for offshore floating fan |
| PCT/CN2023/071061 WO2024007567A1 (en) | 2022-07-06 | 2023-01-06 | Fmeca-based reliability analysis method and apparatus for offshore floating wind turbine |
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| CN202210789641.4A CN115169038B (en) | 2022-07-06 | 2022-07-06 | FMECA-based reliability analysis method and device for offshore floating fan |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7593859B1 (en) * | 2003-10-08 | 2009-09-22 | Bank Of America Corporation | System and method for operational risk assessment and control |
| CN103186708A (en) * | 2011-12-31 | 2013-07-03 | 电子科技大学 | Failure mode effects and criticality analysis method adopting two RPNs |
| CN114116430A (en) * | 2021-12-03 | 2022-03-01 | 中国华能集团清洁能源技术研究院有限公司 | System reliability analysis method, device and equipment |
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| FR2967642B1 (en) * | 2010-11-22 | 2013-08-16 | Nass&Wind Ind | OFFSHORE WIND POWER DEVICE WITH PARTICULAR SEMI-SUBMERSIBLE FLOAT |
| CN108133311A (en) * | 2017-12-14 | 2018-06-08 | 长春工程学院 | A kind of Wind turbines fault mode risk assessment and analysis method for reliability |
| US11030034B2 (en) * | 2019-02-05 | 2021-06-08 | Intel Corporation | Quantitative software failure mode and effects analysis |
| CN115169038B (en) * | 2022-07-06 | 2024-02-09 | 中国华能集团清洁能源技术研究院有限公司 | FMECA-based reliability analysis method and device for offshore floating fan |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7593859B1 (en) * | 2003-10-08 | 2009-09-22 | Bank Of America Corporation | System and method for operational risk assessment and control |
| CN103186708A (en) * | 2011-12-31 | 2013-07-03 | 电子科技大学 | Failure mode effects and criticality analysis method adopting two RPNs |
| CN114116430A (en) * | 2021-12-03 | 2022-03-01 | 中国华能集团清洁能源技术研究院有限公司 | System reliability analysis method, device and equipment |
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