CN106447107A - Maintenance method based on aircraft structure health monitoring - Google Patents
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Abstract
The invention discloses a maintenance method based on aircraft structure health monitoring. The maintenance method based on aircraft structure health monitoring comprises a step 1 of establishing an aircraft database of aircraft condition data; a step 2 of computing, by simulation, the life consumption of an aircraft in the aircraft database and the probability distribution of cracks in a flight process; a step 3 of establishing a maintenance model, classifying the maintenance of an aircraft group according to the operation state of the aircraft group, and classifying the maintenance into first-level maintenance, second-level maintenance and third-level maintenance according to the operation status of the aircraft group; a step 4 of according to the actual operating state of the aircraft group, performing corresponding maintenance in the first-level maintenance, the second-level maintenance and the third-level maintenance on respective aircrafts. The maintenance method based on aircraft structure health monitoring is used for the aircraft group, fully excavate the life potential of the aircraft group in the case of ensuring the normal task of the aircraft group and avoid unnecessary maintenance.
Description
Technical Field
The invention relates to the technical field of fatigue strength of airplane structures, in particular to a maintenance method based on airplane structure health monitoring.
Background
The noun explains:
retention rate: in an aircraft group, at least the ratio of aircraft that can perform a mission immediately (or can perform a mission when necessary) to aircraft in the aircraft group is maintained, that is, the ratio of aircraft that can fly to aircraft that cannot fly (aircraft that cannot fly due to maintenance, failure, damage, or the like).
The safety, reliability, fault diagnosis and prediction, health management, maintenance and the like of modern airplanes are increasingly paid more attention by people. The fault diagnosis and health monitoring are that various data information of a sensor acquisition system is used as less as possible, the health state of the airplane is evaluated by means of various intelligent reasoning algorithms, the fault of the airplane is predicted before the airplane breaks down, and a series of maintenance support measures are provided by combining available resource information to realize the situation maintenance of the airplane. Implementation of fault diagnosis and health monitoring techniques will allow the maintenance that was previously dominated by events (post-event maintenance) or time-dependent maintenance (periodic maintenance) to be replaced by optional maintenance.
The method is not used for directly eliminating the faults of the airplane, but used for knowing and predicting when the faults are likely to occur, so that the purposes of autonomous guarantee, use and guarantee cost reduction are realized, and the safety and the economy of the service of the airplane are considered.
In the prior art, after-repair and regular repair are usually adopted, so that sometimes, an airplane with a fault or a crack cannot be repaired in time, and sometimes, frequent repair is possible, and the cost is wasted.
Accordingly, a technical solution is desired to overcome or at least alleviate at least one of the above-mentioned drawbacks of the prior art.
Disclosure of Invention
It is an object of the present invention to provide a maintenance method based on aircraft structural health monitoring that overcomes or at least alleviates at least one of the above-mentioned drawbacks of the prior art.
In order to achieve the above object, the present invention provides a maintenance method based on aircraft structure health monitoring, which is used for maintaining an aircraft group with a plurality of aircraft, and the maintenance method based on aircraft structure health monitoring comprises the following steps: step 1: establishing an aircraft database of aircraft condition data; step 2: simulating and calculating the service life consumption and the probability distribution condition of cracks of the airplane in the airplane database in the flying process; and step 3: establishing a maintenance model, performing maintenance classification on the aircraft group according to the operating condition of the aircraft group, and classifying the maintenance classification into first-stage maintenance, second-stage maintenance and third-stage maintenance according to the operating state of the aircraft group, wherein the first-stage maintenance comprises the step of optimizing the maintenance model to form a first-stage maintenance model; the second-level maintenance comprises forming a second-level maintenance model by optimizing the maintenance model; the third pole maintenance comprises forming a third pole maintenance model by optimizing the maintenance model; and 4, step 4: and respectively maintaining each airplane by adopting one of primary maintenance, secondary maintenance or tertiary maintenance according to the actual running state of the airplane set.
Preferably, the step 3 specifically comprises: the maintenance model includes a maintenance cost model and a retention rate model.
Preferably, the aircraft condition in step 1 comprises at least: typical key structure finite element analysis data, a fatigue analysis data model, intelligent monitoring measurement data, test flight data and outfield flight parameter data.
Preferably, the step 2 specifically comprises: according to the airplane condition in the airplane database, a neural network load model, a rain flow counting method, a damage calculation formula and a crack propagation probability distribution method are adopted to simulate and calculate the service life consumption and the crack probability distribution condition of the airplane in the airplane database in the flying process.
Preferably, the maintenance cost model is specifically:
for aircraft i first repair crack pile failure time minimum)
Wherein: z is the number of airplanes; i (i ═ 1,2, …, z) denotes the ith aircraft; k is a radical ofiRepresenting the ith aircraft to have k crack points; t _ failurei kRepresents the time to failure of k crack points; m isiRepresenting that the crack is repaired m times; cWaste of lifeRepresenting the life waste coefficient of the crack maintenance unit time; t is tfailureIndicating the time to failure of the crack; t is tfixIndicating repair time for the crack; cShutdownRepresents a single shutdown maintenance cost; m represents the number of stops; t _ fixi jThe repair time for the jth crack of the aircraft i is denoted t _ fixi l(l＝1,…,mi) One of them.
Preferably, the retention rate model is specifically:
wherein: t is time; l is the number of airplanes; l (t) an aircraft in maintenance state at time t; z is the total number of airplanes; p (t) is a retention rate model.
Preferably, the first-stage maintenance is performed by optimizing the maintenance model, and the forming of the first-stage maintenance model specifically includes:
for aircraft i first repair crack pile failure time minimum)
Wherein: z is the number of airplanes; i (i ═ 1,2, …, z) denotes the ith aircraft; k is a radical ofiRepresenting the ith aircraft to have k crack points; t _ failurei kRepresents the time to failure of k crack points; m isiRepresenting that the crack is repaired m times; cWaste of lifeRepresenting the life waste coefficient of the crack maintenance unit time; t is tfailureIndicating the time to failure of the crack; t is tfixIndicating repair time for the crack; cShutdownRepresents a single shutdown maintenance cost; m represents the number of stops; t _ fixi jThe repair time for the jth crack of the aircraft i is denoted t _ fixi l(l＝1,…,mi) One of (a); p (t) is a retention rate function; l (t) an aircraft in maintenance state at time t; z is the total number of airplanes; p _ min is the minimum requirement of retention rate; t is time; l is a flyThe number of machines;
the second-level maintenance is realized by optimizing the maintenance model, and the second-level maintenance model is formed by the following specific steps:
wherein,
l (t) is the airplane in the maintenance state at the time t; z is the total number of airplanes;
and the third-stage maintenance is realized by optimizing the maintenance model, and the third-stage maintenance model is formed by specifically:
failure time in the first repair crack stack for aircraft i is minimal); wherein,
z is the number of airplanes; i (i ═ 1,2, …, z) denotes the ith aircraft; k is a radical ofiRepresenting the ith aircraft to have k crack points; t _ failurei kRepresents the time to failure of k crack points; m isiRepresenting that the crack is repaired m times; cWaste of lifeRepresenting the life waste coefficient of the crack maintenance unit time; t is tfailureIndicating the time to failure of the crack; t is tfixIndicating repair time for the crack; cShutdownRepresents a single shutdown maintenance cost; m represents the number of stops; t _ fixi jThe repair time for the jth crack of the aircraft i is denoted t _ fixi l(l＝1，…，mi) One of (a); p (t) is a retention rate function; l (t) an aircraft in maintenance state at time t; z is the total number of airplanes; p _ min is the minimum requirement of retention rate; t is time; l is the number of aircraft.
Preferably, the first stage repair further comprises optimizing a first stage repair model, thereby forming a first stage optimized model; the second level repair further comprises optimizing a second level repair model, thereby forming a second level optimization model; the third level repair further includes optimizing a third level repair model to form a third level optimization model.
Preferably, the optimizing the first-stage maintenance model so as to form the first-stage optimization model specifically includes:
performing cluster analysis on airplane condition data of each airplane in the airplane group, taking maintenance cost of each airplane in the airplane group as a subsystem, taking the retention rate of the airplane group as a total system, optimizing each subsystem by respectively adopting a genetic algorithm, returning maintenance time adopted by each subsystem obtained by optimization to the total system for coordination, and returning the coordination result of the total system to each subsystem for optimization until the retention rate of the total system meets the requirement;
the second-level maintenance model is optimized, so that a second-level optimization model is formed by specifically:
performing cluster analysis on the aircraft condition data of each aircraft in the aircraft group, and optimizing by adopting a genetic algorithm to obtain a second-level optimization model as follows:
max(ii) a Wherein,
for aircraft i 1 st repair crack class failure time minimum)
l (t) at time tAn aircraft in a service state; z is the total number of airplanes; t _ fixi jRepresents the repair time for the jth crack of the aircraft i;
the third-level maintenance model is optimized to form a third-level optimization model, specifically, the third-level optimization model is solved by adopting a multi-objective evolutionary algorithm, and the following third-level optimization model is obtained:
failure time in the first repair crack stack for aircraft i is minimal); wherein,
z is the number of airplanes; i (i ═ 1,2, …, z) denotes the ith aircraft; k is a radical ofiRepresenting the ith aircraft to have k crack points; t _ failurei kRepresents the time to failure of k crack points; m isiRepresenting that the crack is repaired m times; cWaste of lifeRepresenting the life waste coefficient of the crack maintenance unit time; t is tfailureIndicating the time to failure of the crack; t is tfixIndicating repair time for the crack; cShutdownRepresents a single shutdown maintenance cost; m represents the number of stops; t _ fixi jThe repair time for the jth crack of the aircraft i is denoted t _ fixi l(l＝1,…,mi) One of (a); p (t) is a retention rate function; l (t) an aircraft in maintenance state at time t; z is the total number of airplanes; p _ min is the minimum requirement of retention rate; t is time; l is the number of aircraft.
The maintenance method based on the aircraft structure health monitoring is used for the aircraft unit, the service life potential of the aircraft can be fully excavated under the condition that the normal task of the aircraft unit is guaranteed and the flight safety of each aircraft is guaranteed, and unnecessary maintenance is avoided.
Drawings
Fig. 1 is a schematic flow chart of a maintenance method based on aircraft structure health monitoring according to a first embodiment of the present invention.
Fig. 2 is a schematic diagram of a first-level optimization model in a maintenance method based on aircraft structure health monitoring according to a first embodiment of the invention.
FIG. 3 is a schematic diagram of a second-level optimization model in a maintenance method based on aircraft structure health monitoring according to a first embodiment of the invention.
Detailed Description
In order to make the implementation objects, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be described in more detail below with reference to the accompanying drawings in the embodiments of the present invention. In the drawings, the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The described embodiments are only some, but not all embodiments of the invention. 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. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention. Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate orientations or positional relationships based on those shown in the drawings, and are used merely for convenience in describing the present invention and for simplifying the description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the scope of the present invention.
Fig. 1 is a schematic flow chart of a maintenance method based on aircraft structure health monitoring according to a first embodiment of the present invention.
The maintenance method based on the aircraft structure health monitoring is used for maintaining an aircraft group with a plurality of aircraft, and comprises the following steps:
step 1: establishing an aircraft database of aircraft condition data, wherein in this embodiment, the aircraft condition in step 1 at least includes: typical key structure finite element analysis data, a fatigue analysis data model, intelligent monitoring measurement data, test flight data and outfield flight parameter data.
Step 2: simulating and calculating the life consumption and the probability distribution condition of the cracks of the airplane in the flying process in the airplane database, wherein in the embodiment, the step 2 specifically comprises the following steps: according to the airplane condition in the airplane database, a neural network load model, a rain flow counting method, a damage calculation formula and a crack propagation probability distribution method are adopted to simulate and calculate the service life consumption and the crack probability distribution condition of the airplane in the airplane database in the flying process.
And step 3: establishing a maintenance model, performing maintenance classification on the aircraft group according to the operating condition of the aircraft group, and classifying the maintenance classification into first-stage maintenance, second-stage maintenance and third-stage maintenance according to the operating state of the aircraft group, wherein the first-stage maintenance comprises the step of optimizing the maintenance model to form a first-stage maintenance model; the second-level maintenance comprises forming a second-level maintenance model by optimizing the maintenance model; the third pole repair includes forming a third pole repair model by optimizing the repair model.
In this embodiment, the maintenance model includes a maintenance cost model and a retention rate model, where the maintenance cost model specifically includes:
for aircraft i first repair crack pile failure time minimum)
Wherein: z is the number of airplanes; i (i ═ 1,2, …, z) denotes the ith aircraft; k is a radical ofiRepresenting the ith aircraft to have k crack points; t _ failurei kRepresents the time to failure of k crack points; m isiRepresenting that the crack is repaired m times; cWaste of lifeRepresenting the life waste coefficient of the crack maintenance unit time; t is tfailureIndicating the time to failure of the crack; t is tfixIndicating repair time for the crack; cShutdownRepresents a single shutdown maintenance cost; m represents the number of stops; t _ fixi jThe repair time for the jth crack of the aircraft i is denoted t _ fixi l(l＝1,…,mi) One of them.
In this embodiment, the retention rate model specifically includes:
wherein: t is time; l is the number of airplanes; l (t) an aircraft in maintenance state at time t; z is the total number of airplanes; p (t) is a retention rate model.
In the present embodiment, since the maintenance model includes the maintenance cost model and the retention rate model, it is advantageous to classify the maintenance into the first-stage maintenance, the second-stage maintenance, and the third-stage maintenance according to the maintenance cost model and the retention rate model.
In this embodiment, the first-stage maintenance takes the specified retention rate as a bottom line, and the first-stage maintenance model formed through optimization in consideration of the maintenance cost specifically includes:
for aircraft i first repair crack pile failure time minimum)
Wherein: z is the number of airplanes; i (i ═ 1,2, …, z) denotes the ith aircraft; k is a radical ofiRepresenting the ith aircraft to have k crack points; t _ failurei kRepresents the time to failure of k crack points; m isiRepresenting that the crack is repaired m times; cWaste of lifeRepresenting the life waste coefficient of the crack maintenance unit time; t is tfailureIndicating the time to failure of the crack; t is tfixIndicating repair time for the crack; cShutdownRepresents a single shutdown maintenance cost; m represents the number of stops; t _ fixi jThe repair time for the jth crack of the aircraft i is denoted t _ fixi l(l＝1,…,mi) One of (a); p (t) is a retention rate function; l (t) an aircraft in maintenance state at time t; z is the total number of airplanes; p _ min is the minimum requirement of retention rate; t is time; l is the number of aircraft.
In this embodiment, the second-level maintenance is based on the optimization of the retention rate, and the second-level maintenance model formed through optimization is specifically as follows, regardless of the maintenance cost:
wherein,
l (t) is the airplane in the maintenance state at the time t; z is the total number of aircraft.
In this embodiment, the third-level maintenance comprehensively considers the retention rate and the maintenance cost, and the optimization to form a third-level maintenance model specifically includes:
failure time in the first repair crack stack for aircraft i is minimal); wherein,
z is the number of airplanes; i (i ═ 1,2, …, z) denotes the ith aircraft; k is a radical ofiRepresenting the ith aircraft to have k crack points; t _ failurei kRepresents the time to failure of k crack points; m isiRepresenting that the crack is repaired m times; cWaste of lifeRepresenting the life waste coefficient of the crack maintenance unit time; t is tfailureIndicating the time to failure of the crack; t is tfixIndicating repair time for the crack; cShutdownRepresents a single shutdown maintenance cost; m represents the number of stops; t _ fixi jThe repair time for the jth crack of the aircraft i is denoted t _ fixi l(l＝1,…,mi) One of (a); p (t) is a retention rate function; l (t) an aircraft in maintenance state at time t; z is the total number of airplanes; p _ min is the minimum requirement of retention rate; t is time; l is the number of aircraft.
By adopting the grading mode, different requirements of the aircraft set can be met to the greatest extent, and maintenance can be carried out as required.
Advantageously, in this embodiment, the first level repair further comprises optimizing the first level repair model to form a first level optimized model; the second level repair further comprises optimizing the second level repair model, thereby forming a second level optimized model; the third level repair further includes optimizing the third level repair model to form a third level optimization model.
The first-level maintenance model, the second-level maintenance model and the third-level maintenance model are further optimized because the maintenance modes of the airplanes are divided into two types, one type is maintenance of a major repair factory, the other type is maintenance of a base, when the number of airplanes of the airplane group is large, and some airplanes of the airplane group need maintenance of the major repair factory and some need maintenance of the base, the cost can be further reduced by further optimizing.
Specifically, the first-stage maintenance model is optimized, so that the first-stage optimization model is specifically formed as follows:
the method comprises the steps of clustering and analyzing airplane condition data of each airplane in an airplane group, specifically, clustering each airplane in the airplane group according to constraint conditions (such as the length of cracks, the crack failure time and the like) to obtain the maintenance time of each maintenance point (part needing maintenance) of each airplane, using the maintenance cost of each airplane in the airplane group as a subsystem, using the retention rate of the airplane group as a total system, optimizing each subsystem by respectively adopting a genetic algorithm, returning the maintenance time adopted by each subsystem obtained through optimization to the total system for coordination, and returning the coordination result of the total system to each subsystem for optimization until the retention rate of the total system meets requirements.
For example, the first-stage maintenance model has a limit on the retention rate, and therefore, when the maintenance time of the aircraft is scheduled with the maintenance cost as a target, too many aircraft in the maintenance state may be in the same time, and the retention rate may not meet the requirement. Therefore, the maintenance cost and the retention rate are needed to be coordinated and optimized in the maintenance decision model, and taking an aircraft group with 24 frames as an example, a first-level optimization model is shown in fig. 2.
Referring to fig. 2, in this embodiment, the second-level maintenance model is optimized, so that the second-level optimization model is specifically formed as follows:
performing cluster analysis on the aircraft condition data of each aircraft in the aircraft group, and optimizing by adopting a genetic algorithm to obtain a second-level optimization model as follows:
max(ii) a Wherein,
for aircraft i 1 st repair crack class failure time minimum)
l (t) is the airplane in the maintenance state at the time t; z is the total number of airplanes; t _ fixi jRepresents the repair time for the jth crack of the aircraft i;
in this embodiment, the third-level maintenance model is optimized to form a third-level optimization model, specifically, a multi-objective evolutionary algorithm is used to solve the third-level optimization model, and the following third-level optimization model is obtained:
failure time in the first repair crack stack for aircraft i is minimal); wherein,
z is the number of airplanes; i (i ═ 1,2, …, z) denotes the ith aircraft; k is a radical ofiRepresenting the ith aircraft to have k crack points; t _ failurei kRepresents the time to failure of k crack points; m isiRepresenting that the crack is repaired m times; cWaste of lifeRepresenting the life waste coefficient of the crack maintenance unit time; t is tfailureIndicating the time to failure of the crack; t is tfixIndicating repair time for the crack; cShutdownRepresenting single shutdown dimensionRepairing cost; m represents the number of stops; t _ fixi jThe repair time for the jth crack of the aircraft i is denoted t _ fixi l(l＝1,…,mi) One of (a); p (t) is a retention rate function; l (t) an aircraft in maintenance state at time t; z is the total number of airplanes; p _ min is the minimum requirement of retention rate; t is time; l is the number of aircraft.
And 4, step 4: and respectively maintaining each airplane by adopting one of primary maintenance, secondary maintenance or tertiary maintenance according to the actual running state of the airplane set.
The maintenance method based on the aircraft structure health monitoring is used for the aircraft unit, the service life potential of the aircraft can be fully excavated under the condition that the normal task of the aircraft unit is guaranteed and the flight safety of each aircraft is guaranteed, and unnecessary maintenance is avoided.
Finally, it should be pointed out that: the above examples are only for illustrating the technical solutions of the present invention, and are not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (9)
1. A maintenance method based on aircraft structure health monitoring is used for maintaining an aircraft group with a plurality of aircraft, and is characterized in that the maintenance method based on aircraft structure health monitoring comprises the following steps:
step 1: establishing an aircraft database of aircraft condition data;
step 2: simulating and calculating the service life consumption and the probability distribution condition of cracks of the airplane in the airplane database in the flying process;
and step 3: establishing a maintenance model, performing maintenance classification on the aircraft group according to the operating condition of the aircraft group, and classifying the maintenance classification into first-stage maintenance, second-stage maintenance and third-stage maintenance according to the operating state of the aircraft group, wherein the first-stage maintenance comprises the step of optimizing the maintenance model to form a first-stage maintenance model; the second-level maintenance comprises forming a second-level maintenance model by optimizing the maintenance model; the third pole maintenance comprises forming a third pole maintenance model by optimizing the maintenance model;
and 4, step 4: and respectively maintaining each airplane by adopting one of primary maintenance, secondary maintenance or tertiary maintenance according to the actual running state of the airplane set.
2. The aircraft structure health monitoring-based maintenance method according to claim 1, wherein the step 3 is specifically: the maintenance model includes a maintenance cost model and a retention rate model.
3. The aircraft structure health monitoring-based maintenance method as claimed in claim 2, wherein the aircraft condition in step 1 at least comprises: typical key structure finite element analysis data, a fatigue analysis data model, intelligent monitoring measurement data, test flight data and outfield flight parameter data.
4. The aircraft structure health monitoring-based maintenance method according to claim 3, wherein the step 2 is specifically: according to the airplane condition in the airplane database, a neural network load model, a rain flow counting method, a damage calculation formula and a crack propagation probability distribution method are adopted to simulate and calculate the service life consumption and the crack probability distribution condition of the airplane in the airplane database in the flying process.
5. The aircraft structure health monitoring-based maintenance method according to claim 4, wherein the maintenance cost model is specifically:
wherein: z is the number of airplanes; i (i ═ 1,2, …, z) denotes the ith aircraft; k is a radical ofiRepresenting the ith aircraft to have k crack points; t _ failurei kRepresents the time to failure of k crack points; m isiRepresenting that the crack is repaired m times; cWaste of lifeRepresenting the life waste coefficient of the crack maintenance unit time; t is tfailureIndicating the time to failure of the crack; t is tfixIndicating repair time for the crack; cShutdownRepresents a single shutdown maintenance cost; m represents the number of stops; t _ fixi jThe repair time for the jth crack of the aircraft i is denoted t _ fixi l(l＝1,…,mi) One of them.
6. The aircraft structure health monitoring-based maintenance method according to claim 5, wherein the retention rate model is specifically:
wherein: t is time; l is the number of airplanes; l (t) an aircraft in maintenance state at time t; z is the total number of airplanes; p (t) is a retention rate model.
7. The aircraft structure health monitoring-based maintenance method as claimed in claim 6, wherein the first-stage maintenance is performed by optimizing the maintenance model, and the forming of the first-stage maintenance model specifically comprises:
wherein: z is the number of airplanes; i (i ═ 1,2, …, z) denotes the ith aircraft; k is a radical ofiRepresenting the ith aircraft to have k crack points; t _ failurei kRepresents the time to failure of k crack points; m isiRepresenting that the crack is repaired m times; cWaste of lifeRepresenting the life waste coefficient of the crack maintenance unit time; t is tfailureIndicating the time to failure of the crack; t is tfixIndicating repair time for the crack; cShutdownRepresents a single shutdown maintenance cost; m represents the number of stops; t _ fixi jThe repair time for the jth crack of the aircraft i is denoted t _ fixi l(l＝1,…,mi) One of (a); p (t) is a retention rate function; l (t) an aircraft in maintenance state at time t; z is the total number of airplanes; p _ min is the minimum requirement of retention rate; t is time; l is the number of airplanes;
the second-level maintenance is realized by optimizing the maintenance model, and the second-level maintenance model is formed by the following specific steps:
wherein,
l (t) is an airplane I in a maintenance state at the moment t; z is the total number of airplanes;
and the third-stage maintenance is realized by optimizing the maintenance model, and the third-stage maintenance model is formed by specifically:
wherein,
z is the number of airplanes; i (i ═ 1,2, …, z) denotes the ith aircraft; k is a radical ofiRepresenting the ith aircraft to have k crack points; t _ failurei kRepresents the time to failure of k crack points; m isiRepresenting that the crack is repaired m times; cWaste of lifeRepresenting the life waste coefficient of the crack maintenance unit time; t is tfailureIndicating the time to failure of the crack; t is tfixIndicating repair time for the crack; cShutdownRepresents a single shutdown maintenance cost; m represents the number of stops; t _ fixi jThe repair time for the jth crack of the aircraft i is denoted t _ fixi l(l＝1,…,mi) One of (a); p (t) is a retention rate function; l (t) an aircraft in maintenance state at time t; z is the total number of airplanes; p _ min is the minimum requirement of retention rate; t is time; l is the number of aircraft.
8. The aircraft structure health monitoring-based repair method of claim 7, wherein the first-stage repair further comprises optimizing a first-stage repair model to form a first-stage optimized model; the second level repair further comprises optimizing a second level repair model, thereby forming a second level optimization model; the third level repair further includes optimizing a third level repair model to form a third level optimization model.
9. The aircraft structure health monitoring-based maintenance method according to claim 8, wherein the optimizing the first-stage maintenance model to form the first-stage optimization model specifically comprises:
performing cluster analysis on airplane condition data of each airplane in the airplane group, taking maintenance cost of each airplane in the airplane group as a subsystem, taking the retention rate of the airplane group as a total system, optimizing each subsystem by respectively adopting a genetic algorithm, returning maintenance time adopted by each subsystem obtained by optimization to the total system for coordination, and returning the coordination result of the total system to each subsystem for optimization until the retention rate of the total system meets the requirement;
the second-level maintenance model is optimized, so that a second-level optimization model is formed by specifically:
performing cluster analysis on the aircraft condition data of each aircraft in the aircraft group, and optimizing by adopting a genetic algorithm to obtain a second-level optimization model as follows:
wherein,
l (t) is the airplane in the maintenance state at the time t; z is the total number of airplanes; t _ fixi jRepresents the repair time for the jth crack of the aircraft i;
the third-level maintenance model is optimized to form a third-level optimization model, specifically, the third-level optimization model is solved by adopting a multi-objective evolutionary algorithm, and the following third-level optimization model is obtained:
wherein,
z is the number of airplanes; i (i ═ 1,2, …, z) denotes the ith aircraft; k is a radical ofiRepresenting the ith aircraft to have k crack points; t _ failurei kRepresents the time to failure of k crack points; m isiRepresenting that the crack is repaired m times; cWaste of lifeRepresenting the life waste coefficient of the crack maintenance unit time; t is tfailureIndicating the time to failure of the crack; t is tfixIndicating repair time for the crack; cShutdownRepresents a single shutdown maintenance cost; m represents the number of stops; t _ fixi jThe repair time for the jth crack of the aircraft i is denoted t _ fixi l(l＝1,…,mi) One of (a); p (t) is a retention rate function; l (t) an aircraft in maintenance state at time t; z is the total number of airplanes; p _ min is the minimum requirement of retention rate; t is time; l is the number of aircraft.
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