CN115186013B - Data acquisition and analysis method based on aviation equipment - Google Patents
Data acquisition and analysis method based on aviation equipment Download PDFInfo
- Publication number
- CN115186013B CN115186013B CN202210877163.2A CN202210877163A CN115186013B CN 115186013 B CN115186013 B CN 115186013B CN 202210877163 A CN202210877163 A CN 202210877163A CN 115186013 B CN115186013 B CN 115186013B
- Authority
- CN
- China
- Prior art keywords
- data
- aviation equipment
- index
- aviation
- equipment
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000004458 analytical method Methods 0.000 title claims abstract description 14
- 238000011156 evaluation Methods 0.000 claims abstract description 65
- 238000012360 testing method Methods 0.000 claims abstract description 60
- 238000000034 method Methods 0.000 claims abstract description 24
- 238000004364 calculation method Methods 0.000 claims abstract description 16
- 238000012545 processing Methods 0.000 claims abstract description 10
- 238000011084 recovery Methods 0.000 claims abstract description 9
- 239000011159 matrix material Substances 0.000 claims description 29
- 238000004891 communication Methods 0.000 claims description 22
- 230000005540 biological transmission Effects 0.000 claims description 15
- 238000007781 pre-processing Methods 0.000 claims description 15
- 238000007689 inspection Methods 0.000 claims description 10
- 238000001514 detection method Methods 0.000 claims description 9
- 238000004140 cleaning Methods 0.000 claims description 3
- 238000001914 filtration Methods 0.000 claims description 3
- 238000012216 screening Methods 0.000 claims description 3
- 238000012163 sequencing technique Methods 0.000 claims description 3
- 238000007405 data analysis Methods 0.000 abstract description 2
- 238000002474 experimental method Methods 0.000 abstract 1
- 238000013210 evaluation model Methods 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 238000012937 correction Methods 0.000 description 2
- 238000013480 data collection Methods 0.000 description 2
- 238000011157 data evaluation Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000013507 mapping Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 229910002056 binary alloy Inorganic materials 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000002035 prolonged effect Effects 0.000 description 1
- 230000035939 shock Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000012549 training Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2462—Approximate or statistical queries
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
- G06F16/2228—Indexing structures
- G06F16/2272—Management thereof
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Human Resources & Organizations (AREA)
- General Physics & Mathematics (AREA)
- Databases & Information Systems (AREA)
- Educational Administration (AREA)
- Tourism & Hospitality (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Development Economics (AREA)
- General Business, Economics & Management (AREA)
- Probability & Statistics with Applications (AREA)
- Entrepreneurship & Innovation (AREA)
- Software Systems (AREA)
- Marketing (AREA)
- General Health & Medical Sciences (AREA)
- Fuzzy Systems (AREA)
- Primary Health Care (AREA)
- Mathematical Physics (AREA)
- Computational Linguistics (AREA)
- Health & Medical Sciences (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Remote Sensing (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a data acquisition and analysis method based on aviation equipment, and relates to the technical field of data analysis and processing. The method provided by the invention comprises the following steps: s1, acquiring an index system established according to a preset aviation equipment experience overall scheme; s2, determining a test subject and a data acquisition model according to an index system, and determining test subject data acquisition items and a questionnaire question bank; s3, establishing an aviation equipment data acquisition platform, acquiring flight parameter device data of aviation equipment in experimental subjects and comprehensive service system record data during experiments, and integrating the data; s4, processing the integrated test collection recovery data, carrying out multidimensional query statistics, and ensuring the integrity and accuracy of the test data; s5, associating and binding the processed data with the index system. According to the invention, the evaluation calculation is carried out by combining the index weight and the evaluation method, and the evaluation calculation result of the index system is obtained, so that scientific and effective evaluation is carried out on aviation equipment.
Description
Technical Field
The invention belongs to the technical field of data analysis and processing, and particularly relates to a data acquisition and analysis method based on aviation equipment.
Background
With the rapid development of science and technology, the new generation of weapons is faster and faster, the application of the emerging air assault travel equipment system is also attracting more attention, the evaluation work requirements on the fight efficiency, the system applicability, the system suitability, the system contribution rate and the like of the air assault travel equipment system are also higher and more important are how to effectively evaluate the efficiency, reasonably perform the system test and use the air assault travel equipment system in the training process.
The air assault travel equipment system comprises a plurality of ground equipment, aviation equipment and the like, the equipment system technology is advanced, the construction is more and more complex, the air assault travel equipment system and the state are evaluated, the technical characteristics and the construction characteristics of the air assault travel equipment system are firstly known, the technical state general view of the air assault travel equipment system is mastered, the environment of the mission task and the application of the air assault travel equipment system is clarified, the mapping relation between the technical state and each capability of the air assault travel equipment system is analyzed and researched, and then an air assault travel equipment system evaluation index system, an index processing model and a comprehensive evaluation model can be built. Only if a scientific and effective evaluation index system, a scientific and stable index evaluation model and a comprehensive evaluation model are established, the comprehensive combat capability of the air shock travel equipment system can be evaluated scientifically and reasonably, and a solid foundation is laid for the next step of work.
The existing aviation equipment data acquisition method cannot acquire field test contents effectively and accurately, meanwhile, the traditional acquisition operability is poor, and the aviation equipment cannot be evaluated scientifically and effectively.
Disclosure of Invention
The invention aims to provide an aviation equipment data acquisition and analysis method, which solves the problems that the existing aviation equipment data acquisition method cannot effectively and accurately acquire field test contents, and meanwhile, the traditional acquisition operability is poor and the aviation equipment cannot be scientifically and effectively evaluated.
In order to solve the technical problems, the invention is realized by the following technical scheme:
the invention discloses a data acquisition and analysis method based on aviation equipment, which comprises the following steps:
s1, acquiring an index system established according to a preset aviation equipment experience overall scheme;
s2, determining a test subject and a data acquisition model according to an index system, and determining test subject data acquisition items and a questionnaire question bank;
s3, establishing an aviation equipment data acquisition platform according to the test subject data acquisition items and the questionnaire question library, wherein the aviation equipment data acquisition platform comprises a wireless communication receiving module, data receiving state detection equipment and data state pre-detection equipment;
setting a wireless communication receiving module according to signal strength comparison indexes wirelessly transmitted by the to-be-acquired aviation equipment server, wherein the wireless communication receiving module is connected with the remote to-be-acquired aviation equipment server, and after receiving the signal strength comparison indexes, the wireless communication receiving module performs area division according to different signal strength indexes and stores the receiving strength ranges of data transmitted by the to-be-acquired aviation equipment server in different areas;
the data receiving state detection device is connected with the wireless communication receiving module and is used for measuring the receiving intensity of data sent by the aviation equipment to be acquired once at intervals so as to judge the position of the area where the aviation equipment is positioned;
the data receiving device is respectively connected with the wireless communication receiving module and the data receiving state detecting device, and is used for selecting a target area and receiving data sent by the aviation equipment server in the target area based on all signal intensity comparison indexes sent by the received aviation equipment server according to data acquisition preset requirements, when the data receiving device receives a plurality of data, the area where the aviation equipment is located is divided into n, n+1 and n+2 according to the signal intensity comparison indexes, and in the process of receiving the data of the n, n+1 and n+2
Normally receiving +.The transmission of aviation equipment within the n-zone according to the transmission order>
Data, send ∈>
The data aviation equipment server sends a network interference signal (JAM signal) to collide with other aviation equipment server networks, and after the other aviation equipment server networks receive the collision, the collision counter is increased by one, and the calculation formula is as follows:
the a is the number of times waiting for transmission, and is used for delaying a period of time to retransmit the data, wherein the time is a preset value until a plurality of data are sequentially transmitted to the data receiving equipment;
acquiring flight parameter device data of aviation equipment in a test subject and comprehensive service system record data during the test according to a data acquisition platform, and integrating the data;
s4, processing the integrated test collection recovery data, carrying out multidimensional query statistics, and ensuring the integrity and accuracy of the test data;
s5, associating and binding the processed data with an index system;
s6, according to the binding data index and the index weight, and by combining an index evaluation calculation method, the aviation equipment is evaluated, and an evaluation result is obtained.
Preferably, in the step S4, the test collection recovery data includes test subject collection data, questionnaire data, test personnel information parameters, test site data and aviation equipment collection parameters; and meanwhile, data processing comprises data screening, data cleaning and filtering, data fitting and data prediction.
Preferably, in the step S4, the step of preprocessing all the collected and recovered data to obtain a preprocessing result includes:
s4.1, determining association relations for all acquisition items, questionnaires and final indexes of an index system according to an aviation equipment inspection overall scheme, wherein the association relations comprise one-to-one association relations and many-to-one association relations;
s4.2, according to collected data collected and recovered, combining index requirements and field test subject execution conditions, reasonably expanding according to data distribution conditions, and carrying out data fitting and data prediction, wherein the implementation modes comprise linear fitting, polynomial fitting and data expansion meeting normal distribution, and the implementation modes of the linear fitting of the data are as follows:
A＝Y avg -BX avAg
y＝Bx+A
the data expansion implementation mode meeting normal distribution is as follows:
wherein the collected test data value x obeys probability distribution with a position parameter of mu and a scale parameter of sigma.
S4.3, according to the collected and recovered flight parameter device data of the aviation equipment, performing two-dimensional graphical display playback based on a time axis, and analyzing maneuvering travelling capacity;
s4.4, comprehensively analyzing the intermittent flight time, the frequency of occurrence of vulnerable parts, the failure occurrence rate and the like according to the acquired and recovered comprehensive service system data of the aviation equipment during the test period;
s4.5, carrying out data preprocessing on the acquisition items according to the overall inspection scheme of the aviation equipment and expert evaluation, assigning values to different final indexes, and judging the evaluation level interval to which the acquisition data belong;
and S4.6, performing data preprocessing on the questionnaire data according to different final index data source standards according to the aviation equipment inspection overall scheme and expert evaluation, and judging that the statistical distribution of the questionnaire options is assigned to the data source matrix of the final index.
Preferably, the index weight calculation method in S6 includes an expert direct assignment method and an analytic hierarchy process, specifically:
1) Establishing a hierarchical structure model; dividing decision targets, considered factors and decision objects into a highest layer, a middle layer and a lowest layer according to the interrelationships among the decision targets, the middle layer and the decision objects, and drawing a hierarchy chart;
only one element in the highest layer of the hierarchy chart is generally a preset target or ideal result of analysis problem, and is also called a target layer; the middle layer contains middle links involved in achieving the aim, and can consist of a plurality of layers, including criteria to be considered, sub-criteria, also called criteria layers; the bottom layer includes various measures, decision schemes, etc. that are selectable to achieve the goal, also referred to as a measure layer or scheme layer.
2) Constructing a judgment matrix; for criterion C k A pairwise comparison judgment matrix can be obtained through the comparison of the relative importance among n elements:
a ij for element i and element relative to C k The importance scale of (2) is generally classified into 1, 3, 5, 7 and 9 grades;
3) Hierarchical single sequencing and consistency checking;
the feature vector corresponding to the maximum feature root of the judgment matrix is normalized, and the sum of elements in the normalized feature vector is marked as W after being equal to 1; the element of W is the ranking weight of the relative importance of the same level factor to a certain factor of the previous level factor, and the process is called level list ranking; the consistency check refers to determining the allowable range of inconsistency for a.
4) Checking the total rank and consistency of the layers; calculating the weight of the relative importance of all factors of a certain level to the highest level, namely the total target, sequentially from the highest level to the lowest level, and calculating a consistency index CR, wherein the index CR is as follows:
when CR < 0.1, the consistency of the judgment matrix is generally considered acceptable, otherwise appropriate correction of the judgment matrix is required.
Preferably, in the step S6, the step of evaluating the aviation equipment according to the binding relationship, and the step of obtaining an evaluation result includes:
s6.1, determining the weights of the evaluated objects, the scoring standard, the number of evaluation grades and indexes thereof according to the overall scheme of the aviation equipment inspection and the collected recovery data structure, wherein the evaluated objects are a plurality of systems or scheme sets to be selected;
s6.2, for each evaluated object, obtaining an evaluation value matrix D S Where S represents the subject number under evaluation.
Representing the evaluation score of the ith expert on the index j for the S-th evaluation object;
s6.3, converting the evaluation matrix into a membership weight evaluation matrix by using a membership function;
and S6.4, carrying out evaluation calculation by combining the membership weight evaluation matrix to finally obtain an evaluation value.
The invention has the following beneficial effects:
1. according to the invention, the specific index system is defined, and the test subjects, the acquisition data items, the questionnaire question library and the like are set according to the index system, so that the on-site acquisition data is carried out, and the convenience, accuracy and reliability of the acquisition of on-site test contents are improved. Through data preprocessing, the influence of abnormal extremum on the evaluation result of the aviation equipment is reduced, and for partial difficult repeated test subjects, support is provided for data evaluation through reasonable data fitting and expansion. And binding test data and an index system, and inputting specific test data as evaluation data. And carrying out evaluation calculation by combining the index weight and the evaluation method to obtain an evaluation calculation result of an index system, thereby carrying out scientific and effective evaluation on aviation equipment.
2. According to the invention, the data to be received are sent to be orderly managed by arranging the aviation equipment data acquisition platform, the data receiving equipment normally receives one of the data, network interference signals, namely JAM signals, are sent to the rest aviation equipment servers which send the rest data, so that the rest aviation equipment server networks are collided, after the rest aviation equipment server networks receive the collision, the collision counter is added to be used for delaying a period of time to resend the data until a plurality of data are sequentially sent to the data receiving equipment, so that the received data can be received to the data receiving equipment, and the data receiving is more accurate.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for acquiring and analyzing data based on aviation equipment provided by the invention;
FIG. 2 is a flow chart of data preprocessing based on the data acquisition and analysis method of the aviation equipment provided by the invention;
FIG. 3 is a flow chart of an aircraft equipment evaluation based on the method for acquiring and analyzing data of the aircraft equipment;
fig. 4 is a block diagram of an avionics data collection platform system based on the avionics data collection and analysis method provided by the invention.
Detailed Description
The invention is further described in connection with the following detailed description, in order to make the technical means, the creation characteristics, the achievement of the purpose and the effect of the invention easy to understand.
In the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper", "lower", "inner", "outer", "front", "rear", "both ends", "one end", "the other end", etc. are based on the directions or positional relationships shown in the drawings, are merely for convenience of describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific direction, be configured and operated in the specific direction, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "provided," "connected," and the like are to be construed broadly, and may be fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.
Referring to fig. 1-3, the invention discloses a data acquisition and analysis method based on aviation equipment, which comprises the following steps:
s1, acquiring an index system established according to a preset aviation equipment experience overall scheme;
s2, determining a test subject and a data acquisition model according to an index system, and determining test subject data acquisition items and a questionnaire question bank;
s3, establishing an aviation equipment data acquisition platform according to the test subject data acquisition items and the questionnaire question library, wherein the aviation equipment data acquisition platform comprises a wireless communication receiving module, data receiving state detection equipment and data state pre-detection equipment;
setting a wireless communication receiving module according to signal strength comparison indexes wirelessly transmitted by the to-be-acquired aviation equipment server, wherein the wireless communication receiving module is connected with the remote to-be-acquired aviation equipment server, and after receiving the signal strength comparison indexes, the wireless communication receiving module performs area division according to different signal strength indexes and stores the receiving strength ranges of data transmitted by the to-be-acquired aviation equipment server in different areas;
the data receiving state detection device is connected with the wireless communication receiving module and is used for measuring the receiving intensity of data sent by the aviation equipment to be acquired once at intervals so as to judge the position of the area where the aviation equipment is positioned;
the data receiving device is respectively connected with the wireless communication receiving module and the data receiving state detecting device, and is used for selecting a target area and receiving data sent by the aviation equipment server in the target area based on all signal intensity comparison indexes sent by the received aviation equipment server according to data acquisition preset requirements, when the data receiving device receives a plurality of data, the area where the aviation equipment is located is divided into n, n+1 and n+2 according to the signal intensity comparison indexes, and in the process of receiving the data of the n, n+1 and n+2
Normally receiving +.The transmission of aviation equipment within the n-zone according to the transmission order>
Data, send ∈>
The data aviation equipment server sends a network interference signal (JAM signal) to collide with other aviation equipment server networks, and after the other aviation equipment server networks receive the collision, the collision counter is increased by one, and the calculation formula is as follows:
the a is the number of times waiting for transmission, and is used for delaying a period of time to retransmit the data, wherein the time is a preset value until a plurality of data are sequentially transmitted to the data receiving equipment;
acquiring flight parameter device data of aviation equipment in a test subject and comprehensive service system record data during the test according to a data acquisition platform, and integrating the data;
the areas where a plurality of aviation devices are locatedDividing into n, n+1, n+2, in receiving data of n, n+1, n+2, the accepted data is set according to the area as
The node for transmitting data is the aviation equipment server, the data receiving equipment monitors whether other aviation equipment servers transmit data to the aviation equipment server in the process of receiving the data transmitted by one aviation equipment server, if yes, a JAM signal is transmitted to the following aviation equipment server according to the transmission time, so that the aviation equipment server temporarily stops transmitting the data, after the other aviation equipment server network receives the collision, a collision counter is increased for one time, the data is retransmitted after a delay period, the time is determined by a binary exponential back-off algorithm, when the collision continuously occurs, the delay time is prolonged, when the collision counter is increased to 16, the data is successfully transmitted, the next aviation server is agreed to transmit the data to the subsidiary data receiving equipment, if the collision counter is increased to 16, the data is still not completely transmitted, or the data is successfully transmitted, the problem is indicated, and the data is manually transmitted and received by a professional.
S4, processing the integrated test collection recovery data, carrying out multidimensional query statistics, and ensuring the integrity and accuracy of the test data;
s5, associating and binding the processed data with an index system;
s6, according to the binding data index and the index weight, and by combining an index evaluation calculation method, the aviation equipment is evaluated, and an evaluation result is obtained.
In step S4, the test collection recovery data includes test subject collection data, questionnaire data, test personnel information parameters, test site data and aviation equipment collection parameters; and meanwhile, data processing comprises data screening, data cleaning and filtering, data fitting and data prediction.
In step S4, all the collected and recovered data are subjected to data preprocessing, and the step of obtaining a preprocessing result includes:
s4.1, determining association relations for all acquisition items, questionnaires and final indexes of an index system according to an aviation equipment inspection overall scheme, wherein the association relations comprise one-to-one association relations and many-to-one association relations;
s4.2, according to collected data collected and recovered, combining index requirements and field test subject execution conditions, reasonably expanding according to data distribution conditions, and carrying out data fitting and data prediction, wherein the implementation modes comprise linear fitting, polynomial fitting and data expansion meeting normal distribution, and the implementation modes of the linear fitting of the data are as follows:
A＝Y avg -BX avAg
y＝Bx+A
the data expansion implementation mode meeting normal distribution is as follows:
wherein the collected test data value x obeys probability distribution with a position parameter of mu and a scale parameter of sigma.
S4.3, according to the collected and recovered flight parameter device data of the aviation equipment, performing two-dimensional graphical display playback based on a time axis, and analyzing maneuvering travelling capacity;
s4.4, comprehensively analyzing the intermittent flight time, the frequency of occurrence of vulnerable parts, the failure occurrence rate and the like according to the acquired and recovered comprehensive service system data of the aviation equipment during the test period;
s4.5, carrying out data preprocessing on the acquisition items according to the overall inspection scheme of the aviation equipment and expert evaluation, assigning values to different final indexes, and judging the evaluation level interval to which the acquisition data belong;
and S4.6, performing data preprocessing on the questionnaire data according to different final index data source standards according to the aviation equipment inspection overall scheme and expert evaluation, and judging that the statistical distribution of the questionnaire options is assigned to the data source matrix of the final index.
The index weight calculation method in S6 comprises an expert direct assignment method and an analytic hierarchy process, and specifically comprises the following steps:
1) Establishing a hierarchical structure model; dividing decision targets, considered factors and decision objects into a highest layer, a middle layer and a lowest layer according to the interrelationships among the decision targets, the middle layer and the decision objects, and drawing a hierarchy chart;
only one element in the highest layer of the hierarchy is generally a predetermined target or ideal result of the analysis problem, also called a target layer; the middle layer contains middle links involved in achieving the aim, and can consist of a plurality of layers, including criteria to be considered, sub-criteria, also called criteria layers; the bottom layer includes various measures, decision schemes, etc. that are selectable to achieve the goal, also referred to as a measure layer or scheme layer.
2) Constructing a judgment matrix; for criterion C k A pairwise comparison judgment matrix can be obtained through the comparison of the relative importance among n elements:
a ij for element i and element relative to C k The importance scale of (2) is generally classified into 1, 3, 5, 7 and 9 grades;
3) Hierarchical single sequencing and consistency checking;
the feature vector corresponding to the maximum feature root of the judgment matrix is normalized, and the sum of elements in the normalized feature vector is marked as W after being equal to 1; the element of W is the ranking weight of the same level factor relative importance of a certain factor to the previous level factor, and the process is called level list ranking; whether the hierarchical order sorting can be confirmed or not, and consistency check is needed, wherein the consistency check refers to determining an inconsistent allowable range for A;
wherein, the unique non-zero characteristic root of the n-order consistent matrix is n; the maximum characteristic root lambda of the n-order positive reciprocal matrix A is larger than or equal to n, and A is a consistent matrix if and only if lambda=n;
due to lambda being continuously dependent on a ij The more λ is greater than n, the more serious the A inconsistency is, the smaller the CI the consistency index is calculated with CI, indicating greater consistency. The feature vector corresponding to the maximum feature value is used as a weight vector of the influence degree of the compared factors on a certain factor of an upper layer, and the larger the inconsistency degree is, the larger the judgment error is caused. The degree of inconsistency of a can thus be measured by the magnitude of the lambda-n value. The defined consistency index is:
ci=0, with complete consistency; CI is close to 0, and satisfactory consistency is achieved; the larger the CI, the more serious the inconsistency; to measure the size of CI, a random uniformity index RI is introduced:
| matrix order | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
| RI | 0 | 0 | 0.58 | 0.90 | 1.12 | 1.24 | 1.32 | 1.41 | 1.45 | 1.49 |
4) Checking the total rank and consistency of the layers; calculating the weight of the relative importance of all factors of a certain level to the highest level, namely the total target, sequentially from the highest level to the lowest level, and calculating a consistency index CR, wherein the index CR is as follows:
when CR < 0.1, the consistency of the judgment matrix is generally considered acceptable, otherwise appropriate correction of the judgment matrix is required.
In step S6, the aviation equipment is evaluated according to the binding relationship, and the step of obtaining an evaluation result includes:
s6.1, checking according to aviation equipmentAnd checking the total scheme and the collected recovery data structure, and determining the weights of the evaluated objects, the scoring standard, the number of the evaluation grades and indexes thereof, wherein the evaluated objects are a plurality of systems or scheme sets to be selected, and the scoring standard is a quantitative standard of qualitative indexes. Let the weight vector of each index obtained finally be A i ；
S6.2, for each evaluated object, obtaining an evaluation value matrix D S Where S represents the subject number under evaluation.
Representing the evaluation score of the ith expert on the index j for the S-th evaluation object;
s6.3, converting the evaluation matrix into a membership weight evaluation matrix by using a membership function;
1) Calculating the membership function of the ith index belonging to the class e evaluation level as f e M is the total number of experts;
2) Calculating the membership weight R of the ith index belonging to the class e evaluation level i,e
Z represents the number of system-specified assessment levels. The expression means that the relative weight of the index i belonging to the e-th class is calculated. From this, the membership weight of the index i belonging to any one of the evaluation grades can be obtained;
3) And a membership weight evaluation matrix R consisting of membership weights of m indexes:
row vector of matrix R is calculated as R i ，R i Element R in (a) i，j Representing the membership degree of the index i to the level j;
s6.4, carrying out evaluation calculation by combining the membership weight evaluation matrix:
1) Obtaining an evaluation result vector
E＝(A 1 ，A 2 ，...，A n )[R 1 ，R 2 ，...，R n ] T ＝(e 1 ，e 2 ，...，e z )
2) Mapping the resulting vector to a specific evaluation value
EA＝(e 1 *v 1 ，e 2 *v 2 ，...，e z *v z )
v i Representing an evaluation score corresponding to the i-th class of evaluation level; EA is the final evaluation value.
According to the aviation equipment data acquisition and analysis method, the specific index system is defined, and the test subjects, the acquisition data items, the questionnaire question bank and the like are set according to the index system, so that the on-site acquisition data is carried out, and the convenience, the accuracy and the reliability of the acquisition of on-site test contents are improved. Through data preprocessing, the influence of abnormal extremum on the evaluation result of the aviation equipment is reduced, and for partial difficult repeated test subjects, support is provided for data evaluation through reasonable data fitting and expansion. And binding test data and an index system, and inputting specific test data as evaluation data. And carrying out evaluation calculation by combining the index weight and the evaluation method to obtain an evaluation calculation result of an index system, thereby carrying out scientific and effective evaluation on aviation equipment.
Examples
A GU900Q GSM/GPRS wireless module is adopted as data receiving equipment in an aviation equipment data acquisition platform system; the system supports multipath linkage, provides rich functions such as voice and data services, is an ideal solution for high-speed data transmission and other applications, supports configurable network disconnection reconnection, and needs to test the working condition of a communication receiving module and set the functional characteristics of the communication receiving module before receiving communication, taking GU900 as an example:
first, GU900 operating conditions were tested: AT (automatic Transmission)
Sending an instruction "AT" to the GU900 chip, if "OK" is returned, the chip can normally communicate, otherwise, the chip is not operated;
secondly, setting GU900 functional characteristics: AT+CFUN
Writing the instruction may reset GU900, may choose to enter a certain sleep mode, or may resume all functions;
AT+CFUN＝1
when the chip is in the sleep mode, all the functions of GU900 can be started by writing the AT command, so that the chip enters the mode functions of data receiving and network interference signal transmitting;
shut down GU900: AT+SMSO
GU900 power supply can be turned off by writing an AT+SMSO instruction, but the AT instruction for turning on the power supply is not available, so that the power supply is turned on after intelligent power off;
establishing a connection
The write command at+cipmux=0 module will enter a single link mode, and the module returns during normal operation
+CIPMUX：0
OK
Setting data transmission mode
The write command at+cipmode=0 sets the module to be in a non-transparent mode, and the module returns when in normal operation:
+CIPMUX：0
OK
open a TCP or UDP link command
Write command at+cipstart= "TCP',"192.168.0.208",80, TCP links host, return value during normal operation is:
OK
CONNECTOK
sending data to an opened TCP/UDP link
After the write command AT+CIPSED= "0", "8", "201", "0" is successful, the prompt is output to wait for the user to input data, if the data reach the data length appointed by the user, the TA will start to send to the server immediately; the user can also send data immediately by sending a < ctrl+z > control code;
automatic reception of data
The module does not need to receive data through a command, and after receiving the data, the module can automatically output the condition of receiving the data at the serial port, and the two modes are as follows:
the data receiving condition is divided into two modes:
(1) Data transmission mode:
outputting the received original data (including binary system) directly at the serial port
(2) Normal transmission mode:
first, the receiving condition of the data, such as the link number and the data length, is output at the serial port. Tightening device
The entire data content is then output in the following format:
+IPD.[sconnid>,J<datalen>:rawdata
and finally, receiving the data sent by the aviation equipment.
The foregoing has shown and described the basic principles and main features of the present invention and the advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (5)
1. The data acquisition and analysis method based on the aviation equipment is characterized by comprising the following steps of: the method comprises the following steps:
s1, acquiring an index system established according to a preset aviation equipment experience overall scheme;
s2, determining a test subject and a data acquisition model according to an index system, and determining test subject data acquisition items and a questionnaire question bank;
s3, establishing an aviation equipment data acquisition platform according to the test subject data acquisition items and the questionnaire question library, wherein the aviation equipment data acquisition platform comprises a wireless communication receiving module, data receiving state detection equipment and data state pre-detection equipment;
setting a wireless communication receiving module according to signal strength comparison indexes wirelessly transmitted by the to-be-acquired aviation equipment server, wherein the wireless communication receiving module is connected with the remote to-be-acquired aviation equipment server, and after receiving the signal strength comparison indexes, the wireless communication receiving module performs area division according to different signal strength indexes and stores the receiving strength ranges of data transmitted by the to-be-acquired aviation equipment server in different areas;
the data receiving state detection device is connected with the wireless communication receiving module and is used for measuring the receiving intensity of data sent by the aviation equipment to be acquired once at intervals so as to judge the position of the area where the aviation equipment is positioned;
the data receiving device is respectively connected with the wireless communication receiving module and the data receiving state detecting device, and is used for selecting a target area and receiving data sent by the aviation equipment server in the target area based on all signal intensity comparison indexes sent by the received aviation equipment server according to data acquisition preset requirements, when the data receiving device receives a plurality of data, the area where the aviation equipment is located is divided into n, n+1 and n+2 according to the signal intensity comparison indexes, and in the process of receiving the data of the n, n+1 and n+2
Normally receiving +.The transmission of aviation equipment within the n-zone according to the transmission order>
Data to remaining transmission
The data aviation equipment server sends a network interference signal (JAM signal) to other aviation equipmentThe server network collides, and after other aviation equipment server networks receive the collision, the collision counter is increased by one, and the calculation formula is as follows:
the a is the number of times waiting for transmission, and is used for delaying a period of time to retransmit the data, wherein the time is a preset value until a plurality of data are sequentially transmitted to the data receiving equipment;
acquiring flight parameter device data of aviation equipment in a test subject and comprehensive service system record data during the test according to a data acquisition platform, and integrating the data;
s4, processing the integrated test collection recovery data, carrying out multidimensional query statistics, and ensuring the integrity and accuracy of the test data;
s5, associating and binding the processed data with an index system;
s6, according to the binding data index and the index weight, and by combining an index evaluation calculation method, the aviation equipment is evaluated, and an evaluation result is obtained.
2. The method according to claim 1, wherein in the step S4, the test collection recovery data includes test subject collection data, questionnaire data, test personnel information parameters, test site data, and aviation equipment collection parameters; and meanwhile, data processing comprises data screening, data cleaning and filtering, data fitting and data prediction.
3. The method for collecting and analyzing data based on aviation equipment according to claim 2, wherein the step of preprocessing all collected and recovered data in the step S4 to obtain a preprocessing result includes:
s4.1, determining association relations for all acquisition items, questionnaires and final indexes of an index system according to an aviation equipment inspection overall scheme, wherein the association relations comprise one-to-one association relations and many-to-one association relations;
s4.2, according to collected data collected and recovered, combining index requirements and field test subject execution conditions, reasonably expanding according to data distribution conditions, and carrying out data fitting and data prediction, wherein the implementation modes comprise linear fitting, polynomial fitting and data expansion meeting normal distribution, and the implementation modes of the linear fitting of the data are as follows:
A＝Y avg -BX avAg
y＝Bx+A
wherein X and Y are all collected experimental data variables, B is a preliminary data prediction result, and X i For the ith observation value, A is a component of a reaction relation straight line, and Y is a linear fitting result;
the data expansion implementation mode meeting normal distribution is as follows:
wherein the acquired test data value x obeys probability distribution with the position parameter mu and the scale parameter sigma;
s4.3, according to the collected and recovered flight parameter device data of the aviation equipment, performing two-dimensional graphical display playback based on a time axis, and analyzing maneuvering travelling capacity;
s4.4, comprehensively analyzing the inter-turning flight time, the frequency of occurrence of vulnerable parts and the failure occurrence rate according to the acquired and recovered comprehensive service system data of the aviation equipment during the test period;
s4.5, carrying out data preprocessing on the acquisition items according to the overall inspection scheme of the aviation equipment and expert evaluation, assigning values to different final indexes, and judging the evaluation level interval to which the acquisition data belong;
and S4.6, performing data preprocessing on the questionnaire data according to different final index data source standards according to the aviation equipment inspection overall scheme and expert evaluation, and judging that the statistical distribution of the questionnaire options is assigned to the data source matrix of the final index.
4. The method for acquiring and analyzing data based on aviation equipment according to claim 3, wherein the method for calculating the index weight in S6 comprises an expert direct assignment method and an analytic hierarchy process, specifically:
1) Establishing a hierarchical structure model; dividing decision targets, considered factors and decision objects into a highest layer, a middle layer and a lowest layer according to the interrelationships among the decision targets, the middle layer and the decision objects, and drawing a hierarchy chart;
2) Constructing a judgment matrix; for criterion C k A pairwise comparison judgment matrix can be obtained through the comparison of the relative importance among n elements;
3) Hierarchical single sequencing and consistency checking;
4) Checking the total rank and consistency of the layers; and calculating the weight of the relative importance of all factors of a certain level to the highest level, namely the total target, and calculating the consistency index CR from the highest level to the lowest level in sequence.
5. The method of claim 4, wherein only one element in the highest level of the hierarchy is a predetermined target or an ideal result of the analysis problem, also called a target level; the middle layer contains middle links involved in achieving the aim, and can consist of a plurality of layers, including criteria to be considered, sub-criteria, also called criteria layers; the bottom-most level includes various measures, decision schemes, also referred to as measure layers or scheme layers, that are selectable to achieve the goal.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210877163.2A CN115186013B (en) | 2022-07-25 | 2022-07-25 | Data acquisition and analysis method based on aviation equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210877163.2A CN115186013B (en) | 2022-07-25 | 2022-07-25 | Data acquisition and analysis method based on aviation equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115186013A CN115186013A (en) | 2022-10-14 |
| CN115186013B true CN115186013B (en) | 2023-05-02 |
Family
ID=83521402
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210877163.2A Active CN115186013B (en) | 2022-07-25 | 2022-07-25 | Data acquisition and analysis method based on aviation equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115186013B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116503766B (en) * | 2023-05-25 | 2023-09-12 | 中国人民解放军陆军航空兵学院 | Method for analyzing maneuverability based on flight parameter data of aviation equipment |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR102171502B1 (en) * | 2014-02-27 | 2020-10-29 | 삼성전자 주식회사 | Modulation method and apparatus for tranceiving signal in a mobile communication system |
| CN107872900B (en) * | 2017-10-31 | 2020-06-09 | 西安空间无线电技术研究所 | Satellite channel S-ALOHA access system and method supporting differentiated services |
| CN111553590B (en) * | 2020-04-27 | 2021-09-24 | 中国电子科技集团公司第十四研究所 | Radar embedded health management system |
| CN114202212A (en) * | 2021-12-15 | 2022-03-18 | 北京中科智易科技有限公司 | Chemical defense equipment data acquisition and analysis evaluation method and system |
-
2022
- 2022-07-25 CN CN202210877163.2A patent/CN115186013B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN115186013A (en) | 2022-10-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Charrad et al. | NbClust: an R package for determining the relevant number of clusters in a data set | |
| CN107454105B (en) | Multidimensional network security assessment method based on AHP and grey correlation | |
| US20030023534A1 (en) | Method and apparatus for determining and assessing information to be collected based on information-theoretic measures | |
| CN111222776B (en) | Satellite network coordination situation assessment method and system based on convolutional neural network | |
| CN115186013B (en) | Data acquisition and analysis method based on aviation equipment | |
| CN102467684A (en) | System and method for evaluating comprehensive performance based on improved radar chart | |
| CN112184008A (en) | Base station intelligent energy-saving model evaluation method and system based on analytic hierarchy process | |
| CN108898311A (en) | A kind of data quality checking method towards intelligent distribution network repairing dispatching platform | |
| CN107067341A (en) | A kind of RBFNN electrical power distribution automatization system state operation evaluation methods based on multistage entropy weight | |
| CN104881003A (en) | Effectiveness evaluation method for metering production facilities | |
| CN104461896A (en) | Aerospace system key software evaluation method based on credible attribute | |
| CN104239687A (en) | Reliability modeling and evaluation method based on aerospace product signal transmission path | |
| US20230156043A1 (en) | System and method of supporting decision-making for security management | |
| CN115239115A (en) | Low-earth-orbit satellite control station network measurement and control data transmission resource efficiency evaluation method | |
| CN104331613B (en) | The evaluation method of the communication equipment antijamming capability of multiple types | |
| CN105512465A (en) | Cloud platform safety quantitative evaluation method based on improved VIKOR method | |
| CN106446506A (en) | Multi-method-combined automatic and intelligent prediction method of moonlet state | |
| CN108805471A (en) | Evaluation method for water resources carrying capacity based on the analysis of hybrid system interactively | |
| CN114266289A (en) | Complex equipment health state assessment method | |
| CN117172530A (en) | Enterprise operation risk assessment system and method based on data mining algorithm | |
| CN110348676A (en) | A kind of automation of transformation substations equipment state evaluation method and system | |
| CN110766248B (en) | Workshop artificial factor reliability assessment method based on SHEL and interval intuitionistic fuzzy assessment | |
| CN116452154B (en) | Project management system suitable for communication operators | |
| CN113806343A (en) | Assessment method and system for data quality of Internet of vehicles | |
| CN117172721A (en) | Data flow supervision early warning method and system for financing service |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |