CN103617337A - Method for accessorily analyzing maintenance interval of aircraft - Google Patents
Method for accessorily analyzing maintenance interval of aircraft Download PDFInfo
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- CN103617337A CN103617337A CN201310706577.XA CN201310706577A CN103617337A CN 103617337 A CN103617337 A CN 103617337A CN 201310706577 A CN201310706577 A CN 201310706577A CN 103617337 A CN103617337 A CN 103617337A
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Abstract
The invention discloses a method for accessorily analyzing the maintenance interval of an aircraft. The method is characterized by comprising the following steps of: 1, acquiring the failure data of the actual flight of the aircraft; 2, analyzing the failure data obtained from the step 1 through a mathematic model; 3, collecting the maintenance programs and aircraft type parameters of various reference aircraft types; 4, inputting the aircraft type parameters; 5, comparing to calculate reference data and the aircraft type data, wherein the reference data are the aircraft type parameters of various reference aircraft types; 6, calculating to obtain the reference maintenance interval. The method disclosed by the invention combines the advantages of an aircraft reliability data analysis technology and a case-based reasoning technology and more reasonably, and more objectively and more efficiently provides effective service for maintenance program compiling personnel.
Description
Technical field
The present invention relates to a kind of aircraft maintenance interval aided analysis method, be specifically related to a kind of aircraft maintenance interval aided analysis method based on reliability and CBR, the invention belongs to aeronautical technology field.
Background technology
In the process of establishment maintenance program, the discreet value that maintenance intervals normally draws with experience by experiment, has sizable subjectivity.Existing aircraft reliability data analysis technique and the inference technology based on case (being CBR), aircraft reliability data analysis technique is to have gathered aircraft practical flight data, and by some analysis skills, analyze and draw the reliability data in aircraft practical flight.Inference technology based on case is by collecting the maintenance program information of other type aircrafts, by showing similar maintenance task, offers help to maintenance program authorized personnel.The two all only pays close attention to some aspects, both is not unified to combination, has the one-sidedness of certain degree.
Summary of the invention
For solving the deficiencies in the prior art, the object of the present invention is to provide a kind of aircraft maintenance interval aided analysis method.
In order to realize above-mentioned target, the present invention adopts following technical scheme:
An aircraft maintenance interval aided analysis method, is characterized in that, comprises the steps:
Step 1: the fault data that gathers aircraft practical flight;
Step 2: the data that obtain by mathematics model analysis step 1;
Step 3: collect each with reference to maintenance program and the type parameter of type;
Step 4: input the machine shape parameter;
Step 5: comparing calculation reference data and this machine type data, described reference data is that each is with reference to the type parameter of type;
Step 6: the maintenance intervals that draws reference.
Aforesaid a kind of aircraft maintenance interval aided analysis method, is characterized in that, described mathematical model comprises: normal distribution model, exponential distribution model, Weibull distribution model, lognormal distribution model.
Aforesaid a kind of aircraft maintenance interval aided analysis method, is characterized in that the mathematical formulae of described normal distribution model:
in formula: x is fault data array; μ is the average of fault data array; σ is the variance yields of fault data array.
Aforesaid a kind of aircraft maintenance interval aided analysis method, is characterized in that the mathematical formulae of described exponential distribution model:
x>=0, λ > 0, in formula: x is fault data array; λ is average μ/mono-, that is: λ=1/ μ; μ is the average of fault data array.
Aforesaid a kind of aircraft maintenance interval aided analysis method, is characterized in that the mathematical formulae of described lognormal distribution model:
in formula: x is fault data array; μ is the average of fault data array; σ is the variance yields of fault data array.
Aforesaid a kind of aircraft maintenance interval aided analysis method, is characterized in that, the described type parameter with reference to type and the machine shape parameter include CBR analytical parameters and fail-safe analysis parameter.
Aforesaid a kind of aircraft maintenance interval aided analysis method, is characterized in that, described CBR analytical parameters comprises: type similarity parameter, similarity of tasks parameter and parameter weight definition.
Aforesaid a kind of aircraft maintenance interval aided analysis method, is characterized in that, described step 5 comprises:
Step 5a: by reference to the type similarity parameter of type, type similarity parameter and the weight of this type, calculate the type similarity data between two types;
Step 5b: by reference to the similarity of tasks parameter of type, similarity of tasks parameter and the weight of this type, be combined calculating with type similarity data, draw the similarity of tasks data between two tasks;
Step 5c: analyze type similarity data and similarity of tasks data, whether judgement has reference value with reference to the reference task of type; If be not worth, finish reference; Otherwise, carry out step 5d;
Step 5d: the reliability distribution models that obtains the present analysis parts that draw in step 2;
Step 5e: the maintenance policy of selecting by maintenance program authorized personnel, maintenance angle and analytical parameters;
Step 5f: according to distributed model, maintenance policy, maintenance angle, determine calculative mathematical formulae.
Aforesaid a kind of aircraft maintenance interval aided analysis method, is characterized in that, described step 6 comprises: by mathematical formulae and analytical parameters, calculate the maintenance intervals of reference.
Usefulness of the present invention is: the present invention makes " aircraft reliability data analysis technique " and " inference technology based on case " both advantages, more rationally, more objective, more efficiently for maintenance program authorized personnel provides effective service.
Accompanying drawing explanation
Fig. 1 is a process flow diagram of preferably implementing of the present invention.
Embodiment
Below in conjunction with the drawings and specific embodiments, the present invention is done to concrete introduction.
Shown in Fig. 1, the present invention's principle of work of the present invention is divided into 6 steps:
1. gather the fault data of aircraft practical flight
Gathering the fault data in practical flight, is a most important part in fail-safe analysis.Only have the True Data of having grasped each service parts, real foundation could be provided for analytical work below.
2. by mathematics model analysis data
The invention provides multiple mathematical model, comprising normal distribution model, exponential distribution model, Weibull distribution model, lognormal distribution model etc.In analytic process, calculate successively respectively various distributed models, determine whether the regularity of distribution of fault data meets model.When not meeting, calculate next model and whether meet.
The mathematical formulae of normal distribution model:
in formula: x is fault data array; μ is the average of fault data array; σ is the variance yields of fault data array.
The mathematical formulae of exponential distribution model:
x>=0, in λ > 0 formula: x is fault data array; λ is average μ/mono-, that is: λ=1/ μ; μ is the average of fault data array.
The mathematical formulae of Weibull distribution model:
in formula: x is fault data array; η is the value of phat (1); M is the value of phat (2).
The mathematical formulae of lognormal distribution model:
in formula: x is fault data array; μ is the average of fault data array; σ is the variance yields of fault data array.
3. collect maintenance program and the design parameter of each type
The maintenance program of various type aircrafts, has comprised the most probable maintenance intervals that planemaker provides.The distinctive analytical parameters of each type is the key factor of determining how reference is compared.
4. input the machine shape parameter
For the new architecture that need to work out maintenance program, each has specific analytical parameters.Only have the design parameter of having grasped new architecture, so follow-up analytical work is just meaningful, possesses reference value.
Type parameter and the machine shape parameter with reference to type include CBR analytical parameters and fail-safe analysis parameter.CBR analytical parameters:
(1) type similarity parameter: Gross Weight Takeoff, thrust-weight ratio, Mach Number Never To Be Exceeded, cruise speed, visiting number, ultimate run, maximum load, engine number, engine arrangement (tail hangs, the wing hang), day utilization factor, manufacturer/manufacturer etc.
(2) similarity of tasks parameter: Gross Weight Takeoff, visiting number, day utilization factor, the Deng， supplier of manufacturer/manufacturer, principle of design, inside and outside, fault effects classification etc.
(3) parameter weight definition: be all analytical parameters definition weight separately.
Fail-safe analysis parameter is divided into three kinds of maintenance policies and multiple module, as shown in following table one to three:
Table one: hard time maintenance strategy
Table two: look feelings maintenance policy
Table three: blind detection strategy
5. comparing calculation reference data and this machine type data
(1) pass through the type similarity parameter of the reference type of the 3rd step procedure definition, type similarity parameter and the weight of this type, can calculate the type similarity data between two types.
(2) by reference type similarity of tasks parameter, this type similarity of tasks parameter and the weight of definition, be combined calculating with type similarity data, can draw the similarity of tasks data between two tasks.
(3) analyze type similarity data and similarity of tasks data, whether judgement has reference value with reference to the reference task of type.If be not worth, finish reference; Otherwise, carry out follow-up Analysis of Reliability Data process.
(4) obtain the reliability distribution models of the present analysis parts that draw in second step process.
(5) maintenance policy of selecting by maintenance program authorized personnel, maintenance angle and input analytical parameters.
(6) according to distributed model, maintenance policy, maintenance angle, determine calculative mathematical formulae.
6. draw the maintenance intervals of reference
By mathematical formulae and analytical parameters, calculate the maintenance intervals of reference.
The present invention is by above-mentioned 6 steps, combine the feature of " aircraft reliability data analysis technique " and " inference technology based on case ", make " aircraft reliability data analysis technique " and " inference technology based on case " both advantages, more rationally, more objective, more efficiently for maintenance program authorized personnel provides effective service.
More than show and described ultimate principle of the present invention, principal character and advantage.The technician of the industry should understand, and above-described embodiment does not limit the present invention in any form, and all employings are equal to replaces or technical scheme that the mode of equivalent transformation obtains, all drops in protection scope of the present invention.
Claims (9)
1. an aircraft maintenance interval aided analysis method, is characterized in that, comprises the steps:
Step 1: the fault data that gathers aircraft practical flight;
Step 2: the data that obtain by mathematics model analysis step 1;
Step 3: collect each with reference to maintenance program and the type parameter of type;
Step 4: input the machine shape parameter;
Step 5: comparing calculation reference data and this machine type data, described reference data is that each is with reference to the type parameter of type;
Step 6: the maintenance intervals that draws reference.
2. a kind of aircraft maintenance according to claim 1 interval aided analysis method, is characterized in that, described mathematical model comprises: normal distribution model, exponential distribution model, Weibull distribution model, lognormal distribution model.
3. a kind of aircraft maintenance according to claim 2 interval aided analysis method, is characterized in that the mathematical formulae of described normal distribution model:
in formula: x is fault data array; μ is the average of fault data array; σ is the variance yields of fault data array.
4. a kind of aircraft maintenance according to claim 2 interval aided analysis method, is characterized in that the mathematical formulae of described exponential distribution model:
, x>=0, λ > 0, in formula: x is fault data array; λ is average μ/mono-, that is: λ=1/ μ; μ is the average of fault data array.
5. a kind of aircraft maintenance according to claim 2 interval aided analysis method, is characterized in that the mathematical formulae of described lognormal distribution model:
in formula: x is fault data array; μ is the average of fault data array; σ is the variance yields of fault data array.
6. a kind of aircraft maintenance according to claim 2 interval aided analysis method, is characterized in that, the described type parameter with reference to type and the machine shape parameter include CBR analytical parameters and fail-safe analysis parameter.
7. a kind of aircraft maintenance according to claim 6 interval aided analysis method, is characterized in that, described CBR analytical parameters comprises: type similarity parameter, similarity of tasks parameter and parameter weight definition.
8. according to a kind of aircraft maintenance interval aided analysis method described in claim 1 to 7 any one, it is characterized in that, described step 5 comprises:
Step 5a: by reference to the type similarity parameter of type, type similarity parameter and the weight of this type, calculate the type similarity data between two types;
Step 5b: by reference to the similarity of tasks parameter of type, similarity of tasks parameter and the weight of this type, be combined calculating with type similarity data, draw the similarity of tasks data between two tasks;
Step 5c: analyze type similarity data and similarity of tasks data, whether judgement has reference value with reference to the reference task of type; If be not worth, finish reference; Otherwise, carry out step 5d;
Step 5d: the reliability distribution models that obtains the present analysis parts that draw in step 2;
Step 5e: the maintenance policy of selecting by maintenance program authorized personnel, maintenance angle and analytical parameters;
Step 5f: according to distributed model, maintenance policy, maintenance angle, determine calculative mathematical formulae.
9. a kind of aircraft maintenance according to claim 8 interval aided analysis method, is characterized in that, described step 6 comprises: by described mathematical formulae and analytical parameters, calculate the maintenance intervals of reference.
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| CN105160185A (en) * | 2015-09-14 | 2015-12-16 | 西安航空制动科技有限公司 | Assigning method for factors of affecting mean-time-to repair of aircraft brake system |
| CN107092964A (en) * | 2016-10-31 | 2017-08-25 | 海航航空技术有限公司 | The first inspection control method of aircraft maintenance project |
| CN107563084A (en) * | 2017-09-11 | 2018-01-09 | 中国航空工业集团公司沈阳飞机设计研究所 | A kind of outfield fault information analysis method based on LCA and CATIA systems |
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| CN108038278A (en) * | 2017-11-29 | 2018-05-15 | 安徽四创电子股份有限公司 | A kind of maintenance intervals time formulating method of radar system |
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