CN115860456A - Draught fan reliability analysis method and system based on cost priority number - Google Patents
Draught fan reliability analysis method and system based on cost priority number Download PDFInfo
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Abstract
The application provides a fan reliability analysis method and system based on cost priority number, and the method comprises the following steps: acquiring economic loss data corresponding to faults caused by each fault component in the fan; calculating the fault occurrence probability and the fault undetected probability of each fault component; calculating the cost priority number of each fault part based on the economic loss data, the fault occurrence probability and the fault undetected probability; and determining a target failure component according to the counted cost priority numbers of all failure components, and performing operation and maintenance on the target failure component. The method analyzes the reliability of the fan based on the cost priority number, and improves the objectivity, accuracy and interpretability of the reliability analysis of the fan.
Description
Technical Field
The application relates to the technical field of reliability analysis, in particular to a method and a system for analyzing the reliability of a fan based on cost priority.
Background
With the development of wind power generation technology, the popularity of wind turbine generators is gradually increased, and the types and scales of wind turbine generators are also gradually increased. At present, in a large wind power plant project, a fan is subjected to reliability analysis, possible faults are analyzed, and relevant measures are taken to ensure normal and safe operation of the fan.
In the related art, when reliability Analysis is performed on a fan, a subjective Analysis method is usually adopted, for example, a Failure Mode, influence and Criticality Analysis (Failure Mode, effects and Criticality Analysis, FMECA for short) Analysis method is adopted, and the method quantizes reliability Analysis indexes according to experience of field experts and judges the risk level of the fan by establishing a risk priority number RPN.
However, the reliability analysis result obtained by the above analysis method has too strong subjectivity, the uncertainty degree of the result is large, and the accuracy of the analysis result obtained when the introduced subjective data is inaccurate is low in some cases. Therefore, a scheme capable of improving the objectivity and accuracy of reliability analysis of the fan is urgently needed.
Disclosure of Invention
The present application is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, the first purpose of the application is to provide a fan reliability analysis method based on cost priority, the method is used for carrying out reliability analysis on the fan based on the cost priority, objective data are used in the analysis process, the cost priority is used as a risk level ranking index, subjective evaluation information is avoided, the objectivity, the accuracy and the interpretability of the obtained fan reliability analysis result are improved, and therefore the problems that the reliability analysis result of the traditional FMECA method is strong in subjectivity, large in uncertainty and poor in result interpretability are solved.
A second objective of the present application is to provide a fan reliability analysis system based on cost priority;
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 is to provide a method for analyzing reliability of a wind turbine based on cost priority, where the method includes the following steps:
acquiring economic loss data corresponding to faults caused by each fault component in the fan;
calculating the fault occurrence probability and the fault undetected probability of each fault component;
calculating a cost priority for each of the faulty components based on the economic loss data, the probability of occurrence of the fault, and the probability of undetected fault;
and determining a target failure component according to the counted cost priority numbers of all failure components, and performing operation and maintenance on the target failure component.
Optionally, in an embodiment of the present application, the economic loss data includes a direct economic loss and an indirect economic loss, and the calculating a direct economic loss caused by a fault caused by each faulty component in the wind turbine includes: determining a material cost, a transportation cost, and a maintenance cost resulting from replacing each of the failed components; determining potential cost caused by damage to other components in the fan due to each fault component; adding the material cost, the transportation cost, the repair cost, and the potential cost to obtain the direct economic loss.
Optionally, in an embodiment of the present application, determining the repair cost resulting from replacing each of the failed components comprises: determining the number of maintenance personnel participating in maintenance, the salary of the maintenance personnel and the maintenance time for each fault component; multiplying the number of maintenance personnel, the maintenance personnel pay and the maintenance time to obtain the maintenance cost of each of the faulty components.
Optionally, in an embodiment of the present application, calculating the indirect economic loss caused by the fault caused by each faulty component in the wind turbine includes: determining the output power of the fan where each fault component is located; determining fault shutdown time caused by faults caused by each fault component and electric energy internet access electricity price in a period corresponding to the fault shutdown time; and multiplying the output power, the fault shutdown time and the electric energy grid-surfing electricity price to obtain the indirect economic loss.
Optionally, in an embodiment of the present application, calculating a failure occurrence probability of each of the failed components includes: acquiring fault information statistical data of a target wind power plant to be analyzed, and determining fault frequency statistical data of each fault component from the fault information statistical data; determining the number of fans included in the target wind power plant and the number of parts on each fan; and calculating the product of the number of the fans and the number of the parts, and dividing the failure times statistical data of each failure part by the product to obtain the failure occurrence probability of each failure part.
Optionally, in an embodiment of the present application, calculating the failure undetected probability of each of the failed components includes: acquiring the failure times of each failed component recorded in the maintenance record in a preset time period; acquiring the actual failure times of each failure component; and for each fault component, subtracting the recorded fault times from the actual fault times, and dividing the actual fault times by the recorded fault times to obtain the fault undetected probability of each fault component.
In order to achieve the above object, an embodiment of the second aspect of the present application further provides a reliability analysis system of a wind turbine based on cost priority number, including the following modules:
the acquisition module is used for acquiring economic loss data corresponding to faults caused by each fault component in the fan;
the first calculation module is used for calculating the fault occurrence probability and the fault undetected probability of each fault component;
a second calculation module for calculating a cost priority number of each of the faulty components based on the economic loss data, the fault occurrence probability, and the fault undetected probability;
and the determining module is used for determining a target fault component according to the counted cost priority numbers of all fault components and performing operation and maintenance on the target fault component.
Optionally, in an embodiment of the present application, the economic loss data includes a direct economic loss and an indirect economic loss, and the obtaining module is specifically configured to: determining a material cost, a transportation cost, and a maintenance cost resulting from replacing each of the failed components; determining potential cost caused by damage to other components in the fan due to each fault component; adding the material cost, the transportation cost, the repair cost, and the potential cost to obtain the direct economic loss.
Optionally, in an embodiment of the present application, the obtaining module is specifically configured to: determining the number of maintenance personnel participating in maintenance, the salary of the maintenance personnel and the maintenance time for each fault component; multiplying the number of maintenance personnel, the maintenance personnel pay and the maintenance time to obtain the maintenance cost of each of the faulty components.
The technical scheme provided by the embodiment of the application at least has the following beneficial effects: according to the method and the device, reliability analysis is carried out on the fan based on the cost priority, the cost priority is calculated according to the fault cost, the fault occurrence probability and the fault undetected probability, data which are adopted when the cost priority is calculated are objective data and do not contain any subjective evaluation information, and subjective data such as expert experience are avoided, so that the objectivity and the certainty of the reliability analysis are improved, and the method and the device have high accuracy under different application scenes. The cost priority number obtained by the method is the product of the fault cost, the fault occurrence probability and the fault undetected probability, so that the obtained analysis result is probabilistic and has a definite physical dimension, and the analysis result represents the potential economic loss caused by the fault occurrence, so that the analysis result has interpretability. In addition, the cost priority number calculated by the method takes economy as a first priority principle, reliability analysis of the offshore wind turbine is changed from risk priority to cost priority, and the method has advantages over the risk priority number in aspects of wind turbine development, wind field operation, risk assessment and the like, is favorable for scientificity and economy of wind turbine operation, and improves the yield of wind power generation. Therefore, the reliability analysis method and the reliability analysis device improve the objectivity, the accuracy and the interpretability of the reliability analysis of the fan, are favorable for ensuring the normal and safe operation of the fan, and improve the economical efficiency of the operation of the fan.
In order to implement the foregoing embodiments, the third aspect of the present application further provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method for reliability analysis of a wind turbine based on cost priority number in the foregoing embodiments is implemented.
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 of which:
fig. 1 is a flowchart of a method for analyzing reliability of a wind turbine based on cost priority according to an embodiment of the present disclosure;
FIG. 2 is a flowchart of a method for calculating a direct economic loss caused by a fault according to an embodiment of the present disclosure;
fig. 3 is a flowchart of a method for calculating a failure undetected probability according to an embodiment of the present disclosure;
FIG. 4 is a flowchart of a method for analyzing reliability of a wind turbine based on cost priority according to an embodiment of the present disclosure
Fig. 5 is a schematic structural diagram of a reliability analysis system of a wind turbine based on cost priority numbers according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
The following describes a reliability analysis method and system of a wind turbine based on cost priority number in detail with reference to the accompanying drawings.
Fig. 1 is a flowchart of a reliability analysis method for a wind turbine based on cost priority number according to an embodiment of the present application, and as shown in fig. 1, the method includes the following steps:
and S101, obtaining economic loss data corresponding to faults caused by each fault component in the fan. .
The fans targeted by the reliability analysis method can be various types of fans in practical application, such as land fixed fans or offshore floating fans.
The fault component is a component which has failed in the fan and then causes the fan to fail, and the fault component may be a component or equipment in each system of the fan. In the embodiment of the application, historical data such as the running condition, the fault record and the maintenance record of the fan can be recorded and analyzed, and the fault component causing the fan fault, which is aimed at by the application, is determined.
Specifically, this application confirms earlier the economic loss that the fan trouble caused, promptly the fault cost. The economic loss data mainly comprises two aspects: direct economic losses and indirect economic losses. In practical application, the economic loss data may be already calculated data, the already calculated data may be directly called from a database storing fault data, or data related to each fault may be acquired and then calculated.
The following is an exemplary description of obtaining data related to each fault and calculating direct economic losses and indirect economic losses. Wherein, direct economic loss is the loss that solves this trouble and bring and the loss that causes to fan operation. According to the method and the device, pre-stored historical record data of each fault are obtained, and the economic loss is calculated according to the real historical data.
In order to more clearly illustrate a specific implementation manner of the present application for calculating the direct economic loss caused by the fault, an exemplary description is provided below of a method for calculating the direct economic loss provided in the embodiments of the present application. Fig. 2 is a flowchart of a method for calculating a direct economic loss caused by a fault according to an embodiment of the present application, and as shown in fig. 2, the method includes the following steps:
in step S201, the material cost, transportation cost and maintenance cost resulting from replacing each failed component are determined.
Specifically, for the currently analyzed failed component, the material cost C caused by replacing the lost failed component is searched and calculated in the historical data of the failure caused by the failed component m Transport cost C t And cost of maintenance C r 。
Wherein, the material cost C m Including the cost of a series of processes to produce new replacement parts. Then, the transportation cost C for replacing the failed part is obtained t Including transportation costs to carry away lost, failed components and to carry new replacement components to the wind turbine. Then acquiring labor cost C brought by maintenance personnel to maintain the fault r 。
In particular, in one embodiment of the present application, the material cost C m And cost of transportation C t Can be obtained by directly searching the related data records. In calculating the maintenance cost C r As a possible implementation manner, the number of maintenance personnel participating in maintenance, the salary of the maintenance personnel, and the maintenance time may be determined for the current faulty component, and then the number of maintenance personnel, the salary of the maintenance personnel, and the maintenance time may be multiplied to obtain the maintenance cost. That is, it can be calculated by the following formula:
C r ＝N r ×S r ×T r
wherein N is r For number of maintenance personnel, S r For maintenance staff due to salaries, T r For maintenance time.
It is understood that, in the present embodiment, when the salary and the repair time of each repair person are the same, the repair cost C can be calculated in the above manner r . When the salary of each maintenance personnel is different from the time of participating in maintenance, the maintenance cost of each maintenance personnel can be calculated in sequence, and then the maintenance costs of all the maintenance personnel are added.
Step S202, determining potential cost caused by damage of each fault component to other components in the located fan.
In particular, potential cost C p The cost is brought by damage caused by faults to other parts (mainly mechanical parts and electrical parts) except the fault parts in the fan.
For example, if the current faulty component is a tower drum in the fan support structure system, when the tower drum is tilted or damaged, the tower drum connected to the faulty component may be damaged, and in order to ensure normal operation of the fan, the tower drum may also need to be replaced after a certain time, and the cost caused by subsequent replacement of the tower drum is the potential cost of the fault. For another example, if the current fault component is a generator in a fan electric energy production system, when the output of the generator is abnormal, a rectifier or a transformer in an electric energy conversion system of the fan may be damaged, and in order to ensure normal operation and operation of the fan, the cost brought by subsequent maintenance of the rectifier or the transformer is the potential cost of the fault.
In specific implementation, the potential cost C can be calculated by combining multiple factors such as the fault analysis record of the current fault and the subsequent fault records of related components p 。
Step S203, add the material cost, the transportation cost, the maintenance cost, and the potential cost to obtain the direct economic loss.
Specifically, the direct economic loss L is calculated by the following formula D ：
L D ＝C m +C t +C r +C p 。
Further, indirect economic losses due to faults are recalculated.
Among them, the indirect economic loss is the loss of power generation due to a failed shutdown. And calculating the economic loss caused by unexpected normal power generation due to the current fault according to historical data during the fault shutdown.
In one embodiment of the present application, the indirect economic loss L may be calculated in the following manner I ：
Firstly, the output power P of the fan where each fault component is located is determined by referring to basic information of the fan and the like o 。
Then, by referring to the fault record and the electric energy transaction record and the like, the fault down time T caused by the fault caused by each fault component is determined h And the price P of the electric energy on-line in the current shutdown period r 。
Multiplying the determined output power, the fault shutdown time and the electric energy grid-connection electricity price to obtain the indirect economic loss, namely calculating the indirect economic loss L by the following formula I ：
L I ＝P o ×P r ×T h 。
Further, the total economic loss caused by the fault caused by each fault component can be calculated according to the direct economic loss and the indirect economic loss.
Specifically, the direct economic loss and the indirect economic loss are added to calculate the total economic loss caused by the fault caused by each fault component, that is, the total economic loss L caused by the fault is calculated by the following formula:
L＝L D +L I 。
the total economic loss L is the obtained economic data.
Step S102, calculating the fault occurrence probability and the fault undetected probability of each fault component.
The failure occurrence probability represents the probability of failure occurrence, and can be obtained according to the failure information statistical data.
In one embodiment of the present application, the failure occurrence probability of each failed component may be calculated by:
firstly, acquiring fault information statistical data of a target wind power plant to be analyzed, and determining fault frequency statistical data of each fault component from the fault information statistical data.
Specifically, in this embodiment, a wind farm station including a plurality of wind power generators is used as a research range of reliability analysis, and a fault component in a target wind farm to be subjected to reliability analysis at present is analyzed. And acquiring fault information statistical data of the target wind power plant, wherein the data comprises various fault-related data such as the pre-recorded times, types and maintenance records of all faults occurring in the target wind power plant. And (4) screening out the failure frequency statistical data n of each failure component from the failure information statistical data.
Then, the number of fans included in the target wind farm and the number of parts on each fan are determined. Looking up the data of the target wind power plant and the data of each fan in the wind power plant, and counting the total number T of the fans in the target wind power plant n And the number of parts E on each fan n 。
And finally, calculating the product of the number of the fans and the number of the parts, and dividing the failure frequency statistical data of each failed part by the product to obtain the failure occurrence probability of each failed part. That is, the failure occurrence probability P is calculated by the following formula h ：
Wherein n is the failure frequency statistical data of the failure unit, T n For statistical number of offshore wind turbines, E n The number of the parts counted on a single offshore wind turbine.
Further, a failure undetected probability of each failed component is calculated. The failure undetected probability is determined by the failure times in the maintenance of the parts and the actual failure information.
In order to more clearly illustrate a specific implementation manner of the present application for calculating the failure undetected probability, an exemplary description is given below with reference to a method for calculating the failure undetected probability shown in fig. 3, where as shown in fig. 3, the method includes the following steps:
step S301, obtaining the failure times of each failure component recorded in the maintenance record in a preset time period.
It should be noted that the method for calculating the failure undetected probability may calculate the failure undetected probability of the failed component in one wind turbine, or may study the failure undetected probability of each failed component in one wind farm in the manner described in the foregoing embodiment, and may specifically be determined according to actual factors such as the data analysis amount and the analysis accuracy. In the present embodiment, an offshore wind turbine is taken as a research scope for an exemplary explanation.
Specifically, a maintenance record of the offshore wind turbine is obtained, and the recorded fault frequency RN of the specific parts of the offshore wind turbine in the maintenance within a certain time period is obtained from the maintenance record. The RN represents the number of times of faults of the current fault component which are detected by related personnel and maintained in the maintenance process of the offshore wind turbine, and can be used for representing the number of times of faults which can be detected by the fault component.
Step S302, the actual failure number of each failed component is acquired.
Specifically, the actual failure Frequency (FN) of a specific part of the offshore wind turbine within the preset time period is obtained from the pre-stored historical failure information of the offshore wind turbine, and the historical failure information may be obtained by summarizing actual failures of the wind turbine.
Step S303, for each faulty component, the actual number of faults is subtracted from the recorded number of faults, and then the result is divided by the recorded number of faults, so as to obtain the probability of undetected fault of each faulty component.
Specifically, the failure undetected probability P of each failed component is calculated by the following formula u ：
Step S103, calculating the cost priority number of each fault part based on the economic loss data, the fault occurrence probability and the fault undetected probability.
In the embodiment of the present application, continuing with the description of the example of calculating the total economic loss in step S101, the calculated total economic loss, the failure occurrence probability, and the failure undetected probability are multiplied to calculate the Cost Priority Number, that is, the Cost Priority Number (CPN) of each failed component is calculated by the following formula:
CPN＝L×P h ×P u 。
it is understood that the total economic loss L and the failure occurrence probability P are calculated from the above-described steps h And probability of failure not detected P u The process of calculating the cost priority number CPN is known, the data used for calculating the cost priority number CPN are real historical data which are recorded in advance, the cost priority number CPN is calculated according to objective data generated in practical application, and when risks of all fault parts are analyzed through the cost priority number CPN subsequently, the obtained analysis result has high objectivity and certainty.
And step S104, determining target fault components according to the counted cost priority numbers of all fault components, and performing operation and maintenance on the target fault components.
Specifically, the cost priority number of each fault component participating in the calculation in the above steps is subjected to statistical analysis, a target fault component with a higher risk level is determined according to the cost priority number of each fault component, and then operation and maintenance measures are performed on the target fault component.
As a possible implementation manner, all fault parts are sorted according to the sequence of the CPN values from large to small, and a target fault part with a risk level above a preset risk level threshold is determined according to the sorting result. Wherein the risk level threshold may be a predetermined CPN value, which is used to distinguish between high and low risk levels, and when the calculated CPN value of the faulty unit is greater than the risk level threshold, it indicates that the risk level of the faulty unit is higher. The risk level threshold value can be determined by combining a plurality of modes such as a large number of experimental verifications, experience in practical application, expert knowledge and the like, all the fault components are sorted, the fault components with the CPN values larger than the risk level threshold value are screened out as target fault components, and the number of the target fault components can be one or more.
And then, aiming at the screened target fault components, adopting operation and maintenance measures corresponding to the target fault components to prevent faults. As a possible implementation manner, the fault cause and the scheme for troubleshooting the fault use may be analyzed according to the historical data such as the fault information data and the maintenance record acquired in the above embodiment, and an optimal operation and maintenance scheme for each fault component is determined, for example, the acquired historical fault data, the operation and maintenance data, the operation data after operation and maintenance, and the like of the wind turbine are used as training data, a deep learning neural network model is trained, the optimal operation and maintenance scheme for the target fault component is determined through the trained neural network model, a recommendation and a measure for operation and maintenance are output, and a corresponding operation and maintenance measure is performed on the target fault component, so as to avoid the fault that may occur to the wind turbine.
In summary, according to the reliability analysis method of the fan based on the cost priority number, reliability analysis is performed on the fan based on the cost priority number, the cost priority number is calculated according to the fault cost, the fault occurrence probability and the fault undetected probability, data taken when the cost priority number is calculated are objective data and do not contain any subjective evaluation information, and subjective data such as expert experience is avoided, so that objectivity and certainty of reliability analysis are improved, and higher accuracy is achieved in different application scenes. The cost priority number calculated by the method is the product of the fault cost, the fault occurrence probability and the fault undetected probability, so that the obtained analysis result has the probability and has definite physical dimension, and the analysis result represents the potential economic loss caused by the fault occurrence, so that the analysis result has the interpretability. In addition, the cost priority number calculated by the method takes economy as a first priority principle, the reliability analysis of the offshore wind turbine is changed from risk priority to cost priority, and the method has more advantages than the risk priority number in the aspects of wind turbine development, wind field operation, risk assessment and the like, is favorable for scientificity and economy of wind turbine operation, and improves the yield of wind power generation. Therefore, the method improves the objectivity, the accuracy and the interpretability of the reliability analysis of the fan, is beneficial to ensuring the normal and safe operation of the fan and improves the economical efficiency of the operation of the fan.
In order to more clearly describe the implementation process of the reliability analysis method of the wind turbine based on the cost priority number in the embodiment of the present application, a detailed description is given below with respect to a specific reliability analysis method of the wind turbine based on the cost priority number. Fig. 4 is a flowchart of a specific reliability analysis method for a fan based on cost priority number according to an embodiment of the present application, and as shown in fig. 4, the analysis method according to the embodiment includes the following steps:
step S401: material costs, transportation costs, maintenance costs, and potential costs of damage to other components due to a failure are defined and calculated.
Step S402: direct economic losses were defined and calculated.
Wherein the direct economic loss value is equal to the sum of the material cost, the transportation cost, the maintenance cost and the potential cost in step S401.
Step S403: indirect economic losses are defined and calculated.
Wherein, the indirect economic loss value is equal to the product of the output power of the fan, the price of the power on the internet and the fault downtime S404: and defining and calculating the total economic loss caused by the occurrence of the offshore floating wind turbine fault.
Wherein the total economic loss is equal to the sum of the direct economic loss due to the fault occurrence calculated in step S402 and the indirect economic loss due to the fault occurrence calculated in step S403.
Step S405: and defining and calculating the fault occurrence probability.
Step S406: a failure undetected probability is defined and calculated.
Step S407: defining and calculating cost priority number CPN of the fault of the part, and sorting the CPN values from large to small.
Step S408: suggestions or measures for avoiding the faults are provided.
It should be noted that, for specific implementation manners of each step in this embodiment, reference may be made to the related descriptions in the foregoing embodiments, and details are not described here.
In order to implement the foregoing embodiment, the present application further provides a reliability analysis system for a fan based on cost priority, and fig. 5 is a schematic structural diagram of the reliability analysis system for a fan based on cost priority according to the embodiment of the present application, and as shown in fig. 5, the system includes an obtaining module 100, a first calculating module 200, a second calculating module 300, and a determining module 400.
The obtaining module 100 is configured to obtain economic loss data corresponding to a fault caused by each faulty component in the wind turbine.
The first calculating module 200 is used for calculating the fault occurrence probability and the fault undetected probability of each faulty component.
A second calculating module 300 for calculating a cost priority number of each failed component based on the economic loss data, the failure occurrence probability and the failure undetected probability.
And a determining module 400, configured to determine a target failed component according to the counted cost priority numbers of all failed components, and perform operation and maintenance on the target failed component.
Optionally, in an embodiment of the present application, the economic loss data includes a direct economic loss and an indirect economic loss obtaining module 100, specifically configured to: determining material costs, transportation costs, and maintenance costs incurred to replace each failed component; determining potential cost caused by loss of each fault component to other components in the located fan; adding material costs, transportation costs, maintenance costs and potential costs, direct economic losses are obtained.
Optionally, in an embodiment of the present application, the obtaining module 100 is specifically configured to: determining the number of maintenance personnel participating in maintenance, the salary of the maintenance personnel and the maintenance time for each fault component; and multiplying the number of maintenance personnel, the salaries of the maintenance personnel and the maintenance time to obtain the maintenance cost of each fault component.
Optionally, in an embodiment of the present application, the obtaining module 100 is further configured to: determining the output power of the fan where each fault component is located; determining fault shutdown time caused by faults caused by each fault component and electric energy internet access price in a period corresponding to the fault shutdown time; and multiplying the output power, the fault shutdown time and the electric energy grid-surfing electricity price to obtain indirect economic loss.
Optionally, in an embodiment of the present application, the first calculating module 200 is specifically configured to: acquiring fault information statistical data of a target wind power plant to be analyzed, and determining fault frequency statistical data of each fault component from the fault information statistical data; determining the number of fans included in a target wind power plant and the number of parts on each fan; and calculating the product of the number of the fans and the number of the parts, and dividing the failure times statistical data of each failed part by the product to obtain the failure occurrence probability of each failed part.
Optionally, in an embodiment of the present application, the first computing module 200 is further configured to: acquiring the failure times of each failed component recorded in the maintenance record in a preset time period; acquiring the actual failure times of each failed component; and for each fault component, subtracting the recorded fault times from the actual fault times, and dividing the actual fault times by the recorded fault times to obtain the fault undetected probability of each fault component.
It should be noted that the explanation of the embodiment of the method for analyzing the reliability of the wind turbine based on the cost priority number is also applicable to the system of the embodiment, and is not described herein again.
To sum up, the reliability analysis system of the fan based on the cost priority number according to the embodiment of the present application performs reliability analysis on the fan based on the cost priority number, calculates the cost priority number according to the failure cost, the failure occurrence probability and the failure undetected probability, and adopts objective data as the data taken when calculating the cost priority number, without any subjective evaluation information, thereby avoiding adopting subjective data such as expert experience, and the like, thereby improving objectivity and certainty of reliability analysis, and having higher accuracy in different application scenarios. The cost priority number calculated by the system is the product of fault cost, fault occurrence probability and fault undetected probability, so that the obtained analysis result has probability and definite physical dimension, and the analysis result represents potential economic loss caused by fault occurrence and has interpretability. In addition, the cost priority number calculated by the system takes economy as a first priority principle, the reliability analysis of the offshore wind turbine is changed from risk priority to cost priority, and the system has more advantages than the risk priority number in the aspects of wind turbine development, wind field operation, risk assessment and the like, is favorable for scientificity and economy of wind turbine operation, and improves the yield of wind power generation. Therefore, the system improves the objectivity, the accuracy and the interpretability of the reliability analysis of the fan, is beneficial to ensuring the normal and safe operation of the fan and improves the economical efficiency of the operation of the fan.
In order to implement the above embodiments, the present application further proposes a non-transitory computer-readable storage medium having a computer program stored thereon, where the computer program is executed by a processor to implement the reliability analysis method for a cost-priority-based wind turbine as described in any of the above embodiments.
In the description of the present specification, reference to the description of "one embodiment," "some embodiments," "an example," "a specific example," or "some examples" or the like 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, the schematic representations of the terms used above are not necessarily intended to refer 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. Moreover, various embodiments or examples and features of various embodiments or examples described in this specification can be combined and combined by one skilled in the art without being mutually inconsistent.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless specifically limited 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 steps of a custom logic function or process, and alternate 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 present application.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement 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). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can 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 should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (10)
1. A reliability analysis method of a fan based on cost priority is characterized by comprising the following steps:
acquiring economic loss data corresponding to faults caused by each fault component in the fan;
calculating the fault occurrence probability and the fault undetected probability of each fault component;
calculating a cost priority for each of the failed components based on the economic loss data, the probability of occurrence of the failure, and the probability of undetected failure;
and determining a target fault component according to the counted cost priority numbers of all fault components, and performing operation and maintenance on the target fault component.
2. The reliability analysis method according to claim 1, wherein the economic loss data includes direct economic loss and indirect economic loss, and calculating the direct economic loss caused by the fault caused by each fault component in the wind turbine includes:
determining a material cost, a transportation cost, and a maintenance cost resulting from replacing each of the failed components;
determining potential cost caused by damage to other components in the fan due to each fault component;
adding the material cost, the transportation cost, the maintenance cost, and the potential cost to obtain the direct economic loss.
3. The reliability analysis method of claim 2, wherein determining the repair cost resulting from replacing each of the failed components comprises:
determining the number of maintenance personnel participating in maintenance, the salary of the maintenance personnel and the maintenance time for each fault component;
multiplying the number of maintenance personnel, the maintenance personnel salary and the maintenance time to obtain the maintenance cost of each fault component.
4. The reliability analysis method according to claim 2, wherein calculating the indirect economic loss caused by the fault caused by each fault component in the wind turbine comprises:
determining the output power of the fan where each fault component is located;
determining fault shutdown time caused by faults caused by each fault component and electric energy internet access electricity price in a period corresponding to the fault shutdown time;
and multiplying the output power, the fault shutdown time and the electric energy grid-surfing electricity price to obtain the indirect economic loss.
5. The reliability analysis method according to claim 1, wherein the calculating of the failure occurrence probability of each of the failed components comprises:
acquiring fault information statistical data of a target wind power plant to be analyzed, and determining fault frequency statistical data of each fault component from the fault information statistical data;
determining the number of fans included in the target wind power plant and the number of parts on each fan;
and calculating the product of the number of the fans and the number of the parts, and dividing the failure times statistical data of each failure part by the product to obtain the failure occurrence probability of each failure part.
6. The reliability analysis method according to claim 1, wherein calculating the failure undetected probability of each of the failed components comprises:
acquiring the failure times of each failed component recorded in the maintenance record in a preset time period;
acquiring the actual failure times of each failure component;
and for each fault component, subtracting the recorded fault times from the actual fault times, and dividing the actual fault times by the recorded fault times to obtain the fault undetected probability of each fault component.
7. The utility model provides a reliability analysis system of fan based on cost priority number which characterized in that includes following module:
the acquisition module is used for acquiring economic loss data corresponding to faults caused by each fault component in the fan;
the first calculation module is used for calculating the fault occurrence probability and the fault undetected probability of each fault component;
a second calculation module for calculating a cost priority number of each of the faulty components based on the economic loss data, the fault occurrence probability, and the fault undetected probability;
and the determining module is used for determining a target fault component according to the counted cost priority numbers of all fault components and performing operation and maintenance on the target fault component.
8. The analytical system of claim 7, wherein the economic loss data comprises direct economic losses and indirect economic losses, and the acquisition module is specifically configured to:
determining a material cost, a transportation cost, and a maintenance cost resulting from replacing each of the failed components;
determining potential cost caused by damage to other components in the fan due to each fault component;
adding the material cost, the transportation cost, the repair cost, and the potential cost to obtain the direct economic loss.
9. The analysis system of claim 8, wherein the acquisition module is specifically configured to:
determining the number of maintenance personnel participating in maintenance, the salary of the maintenance personnel and the maintenance time for each fault component;
multiplying the number of maintenance personnel, the maintenance personnel pay and the maintenance time to obtain the maintenance cost of each of the faulty components.
10. A non-transitory computer-readable storage medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements a method for reliability analysis of a cost-priority based wind turbine according to any of claims 1-6.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211334631.8A CN115860456A (en) | 2022-10-28 | 2022-10-28 | Draught fan reliability analysis method and system based on cost priority number |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211334631.8A CN115860456A (en) | 2022-10-28 | 2022-10-28 | Draught fan reliability analysis method and system based on cost priority number |
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| CN115860456A true CN115860456A (en) | 2023-03-28 |
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| CN202211334631.8A Pending CN115860456A (en) | 2022-10-28 | 2022-10-28 | Draught fan reliability analysis method and system based on cost priority number |
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| CN (1) | CN115860456A (en) |
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