CN117933098A - Aeroengine health assessment method based on oil analysis - Google Patents
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Abstract
The invention relates to the technical field of aeroengine fault diagnosis, and discloses an aeroengine health assessment method based on oil analysis, wherein oil data are obtained through a spectrum analysis method, a ferrograph analysis method and a physicochemical analysis method, and a health assessment index system of the aeroengine is established after data processing; the subjective weight is calculated by adopting a three-scale method, so that the calculation complexity is solved, the calculation amount is reduced, the calculation accuracy is improved, the objective weight is calculated by adopting a critic weighting method, the attribute of the data is fully utilized, the distribution of the subjective and objective combination coefficients is balanced by adopting an improved comprehensive weighting method based on the game theory, and the subjective and objective factors of the indexes are fully considered and combined, so that the weight of each index is more scientific and effective; by classifying the health grade, the operation state of the aeroengine is evaluated by using an evaluation model of the health degree, and a reference can be provided for the on-condition maintenance of the aeroengine.
Description
Technical Field
The invention relates to the technical field of fault diagnosis, in particular to an aeroengine health assessment method based on oil analysis.
Background
Due to the characteristics of convenience and rapidness, high-quality service and the like of an airplane, the airplane travel becomes one of the main flow traffic modes selected by most people, along with the high-speed development of aviation industry, the safety problem is more and more important for people, and the safety problem of the aero-engine serving as a core part of the airplane is not neglected; although the aero-engine has extremely high reliability and safety, the harshness of the working environment of the aero-engine and the complexity of the system structure are supposed to be easy to generate faults, so that the detection and maintenance of the aero-engine become an indispensable work, and the regular maintenance detection of the aero-engine has large economic consumption and cannot meet the current maintenance and guarantee requirements, so that the abnormality of the engine work is detected early, and the potential safety hazards are eliminated in a reasonable way, the occurrence of accidents is avoided, so that the aero-engine is an important task for ensuring the flight safety in the current generation; the health evaluation of the aeroengine can know the operation condition of the aeroengine, and has important significance for later maintenance and prediction.
Among the causes of the failure of the aero-engine, the wear is the main cause of the early failure, the best mode of detecting the wear is to detect the oil, the oil analysis technology has smaller interference caused by environmental factors, the method is more reliable, in recent years, domestic and foreign students have made a great deal of researches in the field of health evaluation, kong Xiangxing and the like propose an evaluation method considering the variability of the oil characteristics, cao Guisong and the like propose a fuzzy fusion method to study the wear of the aero-engine, ma Min and the like propose a monitoring method based on CNN-MSLSTM to study the wear of the engine, zhang Guoying and the like propose a SSA optimization SVM method to evaluate the wear. In view of the complexity, gradient and variety of oil indexes of the aero-engine, it is important to give reasonable weights to the indexes, so that the above method is not accurate enough for evaluating the state of the aero-engine. Zhang Xuhan and the like analyze the subjective weighting method and the objective weighting method, and indicate that the subjective weighting method and the objective weighting method are different, and the evaluation result is more reasonable when the subjective weighting method and the objective weighting method are considered simultaneously. Meng Ming et al propose a method for evaluating subjective and objective weights by using an analytic hierarchy process and an entropy weight process, but the conventional analytic hierarchy process requires consistency test, so that the calculated amount is large and the accuracy is reduced. Zhao Xianbao et al propose a weighting method of the entropy correction G1 method to evaluate the operation state of the gearbox, but the magnitude of the entropy value will be pulled down or pulled up to a value of the weight, which results in that the weight cannot be balanced well on some indexes. Han Yajuan et al propose a method for obtaining subjective and objective weights by using a G1 method and a CRITIC method to evaluate the health condition of an aeroengine, and although the G1 method has smaller calculation amount than the analytic hierarchy process, the subjectivity is too strong, so that the weight of one index is larger or smaller than the subjective and objective weight.
Disclosure of Invention
Aiming at various defects in the prior art, the aircraft engine health assessment method based on oil analysis considers the problem of numerous oil indexes of the aircraft engine, obtains final weights based on a combined weighting method of an improved game theory, introduces a concept of relative health degree, carries out state assessment, simplifies calculated amount, has more reasonable weight distribution, and ensures that an assessment result accords with the actual running state of equipment, and is characterized by comprising the following steps:
S1, oil data are obtained through a spectrum analysis method, a ferrograph analysis method and a physicochemical analysis method, data processing is carried out on the oil data, and a plurality of oil evaluation index objects are selected to establish a health evaluation index system of the aeroengine; setting n oil liquid evaluation index objects with m parameter indexes to obtain an n multiplied by m matrix x ij;
S2, constructing a comparison matrix a ij for a plurality of oil evaluation indexes by a three-scale method, judging a matrix b ij, an optimal transmission matrix c ij and a quasi-optimal consistent matrix d ij, and obtaining subjective weight omega 1 by applying a eigenvalue method;
s3, performing just quantization treatment on the oil evaluation index, and obtaining objective weight omega 2 through a critic weighting method;
S4, adopting an improved game theory-based combination weighting method to obtain the weight of each index, balancing the combination coefficient distribution of subjective weight and objective weight, and obtaining the final combination weight omega;
And S5, utilizing the combination weight omega, and evaluating the health degree of the aeroengine by dividing the health grade and adopting a model based on the relative health degree.
In the step S1, oil data are obtained through a spectrum analysis method, a ferrograph analysis method and a physicochemical analysis method, data processing is carried out on the oil data, a plurality of oil evaluation indexes are selected to establish a health evaluation index system of the aeroengine, and specifically, the oil evaluation indexes obtained through the selected spectrum analysis method comprise Fe, cu, ar, mg, ti elements; oil liquid evaluation indexes obtained by a ferrographic analysis method comprise spherical abrasive particles, adhesive abrasive particles, cutting abrasive particles and oxide abrasive particles, and oil liquid evaluation indexes obtained by a physicochemical analysis method comprise viscosity, acid value and impurities, so that the operation state of the aeroengine is evaluated.
In step S2, a comparison matrix a ij is constructed for a plurality of oil evaluation indexes by a three-scale method, a judgment matrix b ij, an optimal transmission matrix c ij and a quasi-optimal consistent matrix d ij are determined, and a eigenvalue method is applied to obtain subjective weight ω 1 specifically as follows:
S201, constructing a comparison matrix a ij by a three-scale method, and comparing all the selected oil liquid evaluation indexes in pairs, wherein when the ith index is not important, the mark scale is 0, and when the ith index is important as the jth index, the mark scale is 1; when the ith index is more important than the jth index, the mark scale is 2;
S202, constructing a judgment matrix:
；
S203, constructing an optimal transfer matrix:
；
s204, constructing a quasi-optimal consistent matrix:
；
Where r i is the sum of the elements of row i in the comparison matrix: ；
r j is the sum of the j-th row elements in the comparison matrix,
R max is the maximum value of the ith row in the comparison matrix:；
r min is the minimum value of the ith row in the comparison matrix: ；
b m is the ratio of r max to r min,
B ik is the value corresponding to the kth column of the ith row in the judgment matrix,
B jk is a value corresponding to the kth column of the jth row in the judgment matrix;
s205, calculating subjective weight omega 1 by using a eigenvalue method.
In step S3, the oil evaluation index is subjected to a quantization process, and objective weight ω 2 is obtained by a critic weighting method, specifically:
s301, carrying out normalization processing on the x ij to obtain a matrix y ij;
；
s302, calculating standard deviation sigma j of each index by using a matrix y ij;
；
is the average value of n y ij,
；
S303, calculating a correlation coefficient r jj′ between the j index and the j' index by using a matrix y ij;
；
s304, calculating the total conflict f j between the j index and all indexes;
；
S305, calculating the information quantity c j contained in the j index;
；
s306, calculating an objective weight omega 2;
。
In the step S4, an improved game theory-based combined weighting method is adopted to obtain the weight of each index, and the combination coefficient distribution of the subjective weight and the objective weight is balanced, so that the final combination weight ω is specifically:
S401, determining an optimization model:
；
Wherein ω i and ω j are the first to second weight vectors, respectively, L is the number of weight vectors, For the coefficients of the combining weights, s.t represents the constraint of the formula;
s402, solving a model, constructing a Lagrange function and deriving:
；
；
Wherein lambda is an unknown introduced by the Lagrangian function;
s403, pair Normalization is carried out, wherein the normalization result of the subjective weight is/>Normalized result of objective weight is/>：
；
S404, calculating to obtain the final combination weight omega:
。
In the step S5, the health degree of the aero-engine is evaluated by using a model based on the relative health degree by classifying the health grades by using the combination weight ω, which specifically includes: dividing the operation state of the aero-engine into five health grades;
s501, normalizing the matrix x ij to obtain a normalized matrix k ij:
；
S502, calculating the relative health degree of the health state of the aero-engine:
HD=kω=k1ω1´+k2ω2´+···+knωn´
Wherein, (omega 1´、ω2´ ···ωn´) is n oil liquid evaluation index objects, (k 1、k2 ···kn) is the numerical value of n oil liquid evaluation indexes in a standardized matrix k ij, F is a health function, HD is the relative health degree of the health state of the aero-engine, and the numerical value is between 0 and 1.
Compared with the prior art, the invention has the following beneficial technical effects and advantages:
The invention provides a scientific and accurate aircraft engine health evaluation system, which considers the problem of numerous oil indexes of an aircraft engine by largely summarizing previous experience, adopts a three-scale method and a critic weighting method to obtain subjective and objective weights, makes full use of the attributes of data, balances the distribution of subjective and objective combination coefficients by an improved comprehensive weighting method based on game theory, fully considers the subjective and objective factors of the indexes and combines the subjective and objective factors, and makes the weights of the indexes more scientific and effective; and a concept of relative health degree is introduced to evaluate the state, the method simplifies the calculated amount, the weight distribution is more reasonable, and the evaluation result accords with the actual running state of the equipment.
Detailed Description
The present invention will be described in detail below: the invention provides an aircraft engine health assessment method based on oil analysis, which comprises the following steps:
S1, oil data are obtained through a spectrum analysis method, a ferrograph analysis method and a physicochemical analysis method, data processing is carried out on the oil data, and a plurality of oil evaluation index objects are selected to establish a health evaluation index system of the aeroengine;
the oil index is obtained by a spectrum analysis method, a ferrograph analysis method and a physicochemical analysis method, and the health state of the aeroengine is analyzed; the spectrum analysis technology is to detect the type and the content of metal according to the spectrum of specific wavelength emitted by various metal abrasive particles in oil liquid when excited in an ionic state, so that the concentration values of different elements can be obtained, the particle detected by the detection method is generally below 10mm, and the analysis efficiency of the abrasive particles with the particle size of 0.01 mm-1 mm is high; the iron spectrum analysis technology is that abrasive particles are separated from oil liquid through a high-gradient strong magnetic field, and the morphology, the size, the number, the components and the distribution of the particles are analyzed to obtain the relative number of different types of particles, and the analysis size range of the detection method is 0.1 mm-1000 mm; the physicochemical analysis technology starts from the quality of the oil liquid itself, and the quality of the oil liquid can be monitored by using a physicochemical method.
Because of numerous oil indexes, fe, cu, ar, mg, ti elements obtained by a spectrum analysis method are selected in the embodiment; the method comprises the steps that the operation state of an aeroengine is evaluated by 12 oil liquid evaluation index objects, namely, 12 oil liquid evaluation index objects with m parameter indexes, obtained by a ferrographic analysis method, namely, viscosity, acid value and impurities, obtained by a physicochemical analysis method, so as to obtain a matrix x ij with the size of 12 x m;
S2, constructing a comparison matrix a ij for a plurality of oil evaluation indexes by a three-scale method, judging a matrix b ij, an optimal transmission matrix c ij and a quasi-optimal consistent matrix d ij, and obtaining subjective weight omega 1 by applying a eigenvalue method; the traditional analytic hierarchy process adopts a nine-scale method to construct a comparison matrix, the two indexes are required to be compared, and each judgment matrix is required to be subjected to consistency test, and the test process is complex and difficult, so that a three-scale (0, 1, 2) method is used for constructing the comparison matrix and the quasi-optimal consistency matrix, the judgment matrix is not required to be subjected to consistency test, a plurality of calculation amounts are reduced, and the calculation accuracy is improved.
S201, constructing a comparison matrix a ij by a three-scale method, and comparing all the selected oil liquid evaluation indexes in pairs, wherein when the ith index is not important, the mark scale is 0, and when the ith index is important as the jth index, the mark scale is 1; when the ith index is more important than the jth index, the mark scale is 2;
S202, constructing a judgment matrix:
；
S203, constructing an optimal transfer matrix:
；
s204, constructing a quasi-optimal consistent matrix:
；
Where r i is the sum of the elements of row i in the comparison matrix: ；
r j is the sum of the j-th row elements in the comparison matrix,
R max is the maximum value of the ith row in the comparison matrix:；
r min is the minimum value of the ith row in the comparison matrix: ；
b m is the ratio of r max to r min,
B ik is the value corresponding to the kth column of the ith row in the judgment matrix,
B jk is a value corresponding to the kth column of the jth row in the judgment matrix;
s205, calculating subjective weight omega 1 by using a eigenvalue method.
S3, performing just quantization treatment on the oil evaluation index, and obtaining objective weight omega 2 through a critic weighting method;
s301, carrying out normalization processing on the x ij to obtain a matrix y ij;
；
s302, calculating standard deviation sigma j of each index by using a matrix y ij;
；
is the average value of n y ij,
；
S303, calculating a correlation coefficient r jj′ between the j index and the j' index by using a matrix y ij;
；
s304, calculating the total conflict f j between the j index and all indexes;
；
S305, calculating the information quantity c j contained in the j index;
；
s306, calculating an objective weight omega 2;
。
S4, adopting an improved game theory-based combination weighting method to obtain the weight of each index, balancing the combination coefficient distribution of subjective weight and objective weight, and obtaining the final combination weight omega;
S401, determining an optimization model:
；
Wherein omega i and omega j are respectively a first weight vector and a second weight vector, L is the number of weight vectors, For the coefficients of the combining weights, s.t represents the constraint of the formula;
s402, solving a model, constructing a Lagrange function and deriving:
；
；
Wherein lambda is an unknown introduced by the Lagrangian function;
s403, pair Normalization is carried out, wherein the normalization result of the subjective weight is/>Normalized result of objective weight is/>：
；
S404, calculating to obtain the final combination weight omega:
；
S5, utilizing the combination weight omega, and evaluating the health degree of the aeroengine by dividing the health grade and adopting a model based on the relative health degree; dividing the operation state of the aero-engine into five health grades;
s501, normalizing the matrix x ij to obtain a normalized matrix k ij:
；
S502, calculating the relative health degree of the health state of the aero-engine:
HD=kω=k1ω1´+k2ω2´+···+k12ωn´
wherein, (omega 1´、ω2´ ···ωn´) is n oil liquid evaluation index objects, (k 1、k2 ···k12) is the numerical value of twelve oil liquid evaluation indexes in a standardized matrix k ij, F is a health function, HD is the relative health degree of the health state of the aero-engine, and the numerical value is between 0 and 1.
The foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the invention are intended to be included within the scope of the invention.
Claims (6)
1. An aircraft engine health assessment method based on oil analysis is characterized by comprising the following steps:
S1, oil data are obtained through a spectrum analysis method, a ferrograph analysis method and a physicochemical analysis method, data processing is carried out on the oil data, and a plurality of oil evaluation index objects are selected to establish a health evaluation index system of the aeroengine; setting n oil liquid evaluation index objects with m parameter indexes to obtain an n multiplied by m matrix x ij;
S2, constructing a comparison matrix a ij for a plurality of oil evaluation indexes by a three-scale method, judging a matrix b ij, an optimal transmission matrix c ij and a quasi-optimal consistent matrix d ij, and obtaining subjective weight omega 1 by applying a eigenvalue method;
s3, performing just quantization treatment on the oil evaluation index, and obtaining objective weight omega 2 through a critic weighting method;
S4, adopting an improved game theory-based combination weighting method to obtain the weight of each index, balancing the combination coefficient distribution of subjective weight and objective weight, and obtaining the final combination weight omega;
And S5, utilizing the combination weight omega, and evaluating the health degree of the aeroengine by dividing the health grade and adopting a model based on the relative health degree.
2. The aircraft engine health assessment method based on oil analysis of claim 1, wherein: in the step S1, oil data are obtained through a spectrum analysis method, a ferrograph analysis method and a physicochemical analysis method, data processing is carried out on the oil data, a plurality of oil evaluation indexes are selected to establish a health evaluation index system of the aeroengine, and specifically, the oil evaluation indexes obtained through the selected spectrum analysis method comprise Fe, cu, ar, mg, ti elements; oil liquid evaluation indexes obtained by a ferrographic analysis method comprise spherical abrasive particles, adhesive abrasive particles, cutting abrasive particles and oxide abrasive particles, and oil liquid evaluation indexes obtained by a physicochemical analysis method comprise viscosity, acid value and impurities, so that the operation state of the aeroengine is evaluated.
3. The aircraft engine health assessment method based on oil analysis of claim 1, wherein: in step S2, a comparison matrix a ij is constructed for a plurality of oil evaluation indexes by a three-scale method, a judgment matrix b ij, an optimal transmission matrix c ij and a quasi-optimal consistent matrix d ij are determined, and a eigenvalue method is applied to obtain subjective weight ω 1 specifically as follows:
S201, constructing a comparison matrix a ij by a three-scale method, and comparing all the selected oil liquid evaluation indexes in pairs, wherein when the ith index is not important, the mark scale is 0, and when the ith index is important as the jth index, the mark scale is 1; when the ith index is more important than the jth index, the mark scale is 2;
S202, constructing a judgment matrix:
；
S203, constructing an optimal transfer matrix:
；
s204, constructing a quasi-optimal consistent matrix:
；
Where r i is the sum of the elements of row i in the comparison matrix: ；
r j is the sum of the j-th row elements in the comparison matrix,
R max is the maximum value of the ith row in the comparison matrix:；
r min is the minimum value of the ith row in the comparison matrix: ；
b m is the ratio of r max to r min,
B ik is the value corresponding to the kth column of the ith row in the judgment matrix,
B jk is a value corresponding to the kth column of the jth row in the judgment matrix;
s205, calculating subjective weight omega 1 by using a eigenvalue method.
4. The aircraft engine health assessment method based on oil analysis of claim 1, wherein:
In step S3, the oil evaluation index is subjected to a quantization process, and objective weight ω 2 is obtained by a critic weighting method, specifically:
s301, carrying out normalization processing on the x ij to obtain a matrix y ij;
；
s302, calculating standard deviation sigma j of each index by using a matrix y ij;
；
Average of n y ij
；
S303, calculating a correlation coefficient r jj′ between the j index and the j' index by using a matrix y ij;
；
s304, calculating the total conflict f j between the j index and all indexes;
；
S305, calculating the information quantity c j contained in the j index;
；
s306, calculating an objective weight omega 2;
。
5. The aircraft engine health assessment method based on oil analysis of claim 1, wherein: in the step S4, an improved game theory-based combined weighting method is adopted to obtain the weight of each index, and the combination coefficient distribution of the subjective weight and the objective weight is balanced, so that the final combination weight ω is specifically:
S401, determining an optimization model:
；
Wherein omega i and omega j are respectively a first weight vector and a second weight vector, L is the number of weight vectors, For the coefficients of the combining weights, s.t represents the constraint of the formula;
s402, solving a model, constructing a Lagrange function and deriving:
；
；
Wherein lambda is an unknown introduced by the Lagrangian function;
s403, pair Normalization is carried out, wherein the normalization result of the subjective weight is/>Normalized result of objective weight is/>：
；
S404, calculating to obtain the final combination weight omega:
。
6. The aircraft engine health assessment method based on oil analysis of claim 1, wherein: in the step S5, the health degree of the aero-engine is evaluated by using a model based on the relative health degree by classifying the health grades by using the combination weight ω, which specifically includes: dividing the operation state of the aero-engine into five health grades;
s501, normalizing the matrix x ij to obtain a normalized matrix k ij:
；
S502, calculating the relative health degree of the health state of the aero-engine:
HD=kω= k1ω1´+ k2ω2´+···+knωn´，
Wherein, (omega 1´、ω2´ ···ωn´) is n oil liquid evaluation index objects, (k 1、k2 ···kn) is the numerical value of n oil liquid evaluation indexes in a standardized matrix k ij, F is a health function, HD is the relative health degree of the health state of the aero-engine, and the numerical value is between 0 and 1.
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