CN115359686A - Instrument landing system signal analysis and diagnosis method and device and electronic equipment - Google Patents
Instrument landing system signal analysis and diagnosis method and device and electronic equipment Download PDFInfo
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Abstract
The invention discloses a method, a device and electronic equipment for analyzing and diagnosing instrument landing system signals, wherein the method comprises the following steps: s1, reading DDM indicating data and longitude and latitude data of a course in an airplane to draw a microampere curve graph A reflecting the deviation degree of the course in a microampere wave coordinate system of the course; s2, drawing a microampere curve chart B reflecting the deviation degree of the glidepath in a glidepath microampere fluctuation coordinate system according to the glidepath indication data; s3, obtaining course signal fluctuation data in a course microampere fluctuation coordinate system; and obtaining glide-slope signal fluctuation data in the glide-slope microampere fluctuation coordinate system. The method can trace the time, the position and the signal structure change of a single event, realize the discovery of the event occurrence rule through statistical analysis, enhance the daily monitoring capability of an operation unit on ILS space signals, provide support for the subsequent flight verification decision and improve the safety operation guarantee capability of a navigation system.
Description
Technical Field
The invention relates to the field of civil aviation flight signal safety, in particular to a method and a device for analyzing and diagnosing signals of an instrument landing system and electronic equipment.
Background
An instrument landing system (ILS for short) is a key blind landing navigation device of the precise approach landing stage of the common equipment in the airport in China at present, and the stable operation of the system is very important for the flight safety. However, with the great increase of the number of flights, signal interference and jitter occur in most domestic airports, and the final approach landing safety is seriously influenced. Daily monitoring of ILS space signals is always a great problem, and mainly depends on ground monitoring tests of equipment and signal quality reports of a unit, from historical events, the unit reports unstable signals of an instrument landing system due to various reasons, including unstable signals caused by faults of instrument landing signals, interference of moving objects on the signals at specific time or at specific positions, interference of other radio equipment transmission or unit operation, and the like. In order to ensure that an instrument landing system provides a correct and reliable guide signal, flight verification, internal signal monitoring and inspection and external field test of fixed time are required; at present, when a unit reports that an instrument landing system signal is unstable, the existing processing method mainly comprises the steps of conducting on-site investigation, analysis and investigation by relevant departments organized by a supervision authority, checking navigation equipment, evaluating an electromagnetic environment, and applying flight verification to analyze relevant technical indexes when necessary. The problems of multiple departments, heavy work task, high labor cost for calling, long analysis time, high consumption cost and the like exist in the flight verification and the current signal monitoring and checking means; the outfield test is generally time-tight, the task is heavy, the working personnel are very easy to have fatigue operation, and in addition, the safety hazards such as runway FOD are easily caused due to the fact that the working personnel carry more equipment and tools. When unstable conditions such as signal jitter occur in the instrument landing system, due to the lack of effective inspection means on the ground and the fact that the feedback of the unit is changed, judgment is difficult, so how to perform effective signal analysis and diagnosis of the instrument landing system is a technical problem which needs to be solved urgently at present.
Disclosure of Invention
Aiming at the technical problems pointed out by the background technology, the invention aims to provide a method, a device and electronic equipment for analyzing and diagnosing the signal of an instrument landing system, which can analyze the signal trend change of the instrument landing system through big data, assist in judging the landing operation condition of the instrument, provide a means for monitoring the operation of the instrument landing system, enhance the daily monitoring capability of an operation unit on ILS space signals, provide support for subsequent flight verification decisions and improve the safe operation guarantee capability of a navigation system.
The purpose of the invention is realized by the following technical scheme:
in a first aspect, the present invention provides a method for analyzing and diagnosing a signal of an instrument landing system, where the method includes:
s1, constructing a course microampere fluctuation coordinate system taking a distance from a course station and a deviation pointer driving current as horizontal and vertical coordinates, drawing a course nominal microampere line and a course microampere boundary line of aircraft landing on the course microampere fluctuation coordinate system, reading course DDM indicating data and longitude and latitude data in the aircraft, and drawing a microampere curve chart A reflecting the deviation degree of the course in the course microampere fluctuation coordinate system;
s2, constructing a glidepath deviation coordinate system taking the distance from a runway entrance and the corrected sea pressure height as horizontal and vertical coordinates, reading glidepath DDM indicating data, longitude and latitude data and height data in the airplane, and drawing the glidepath indicating data in the glidepath deviation coordinate system; constructing a glidepath microampere fluctuation coordinate system taking the horizontal distance from a runway entrance and the driving current of a deviation pointer as horizontal and vertical coordinates, drawing a glidepath nominal microampere line and a glidepath microampere boundary line of the airplane landing on the glidepath microampere fluctuation coordinate system, and drawing a microampere curve chart B reflecting the deviation degree of the glidepath in the glidepath microampere fluctuation coordinate system according to glidepath indication data;
s3, finding a course signal fluctuation mutation area in the microampere curve chart A in the course microampere fluctuation coordinate system and obtaining course signal fluctuation data; finding out the fluctuation mutation area of the glide slope signal in the microampere curve chart B in the glide slope microampere fluctuation coordinate system and obtaining glide slope signal fluctuation data.
In order to better realize the method for analyzing and diagnosing the instrument landing system signal, in the step S3, a deviation microampere threshold A10 of a microampere curve chart A and a nominal microampere line of a course is set, a deviation microampere value A11 of the microampere curve chart A and the nominal microampere line of the course is calculated, the deviation microampere value A11 is compared with the deviation microampere threshold A10, and an area, exceeding the deviation microampere threshold A10, of the deviation microampere value A11 is used as a signal fluctuation mutation area of the course and corresponding signal fluctuation data of the course is obtained; setting a relation microampere threshold A20 between the microampere curve chart A and a course microampere boundary line, calculating a risk microampere distance value A21 of the microampere curve chart A and the course microampere boundary line, comparing the risk microampere distance value A21 with the relation microampere threshold A20, and taking a region where the risk microampere distance value A21 breaks through the relation microampere threshold A20 as a course signal fluctuation mutation region to obtain corresponding course signal fluctuation data.
Preferably, in step S3, the method for analyzing and diagnosing signals of an instrument landing system of the present invention sets a deviation microampere threshold B10 between the microampere graph B and the nominal microampere line of the lower chute, calculates a deviation microampere value B11 between the microampere graph B and the nominal microampere line of the lower chute, compares the deviation microampere value B11 with the deviation microampere threshold B10, and takes a region where the deviation microampere value B11 exceeds the deviation microampere threshold B10 as a fluctuation abrupt change region of the lower chute signal to obtain corresponding fluctuation data of the lower chute signal; setting a relation microampere threshold B20 between the microampere curve chart B and a lower slide microampere boundary line, calculating a risk microampere distance value B21 of the microampere curve chart B and the lower slide microampere boundary line, comparing the risk microampere distance value B21 with the relation microampere threshold B20, and taking a region where the risk microampere distance value B21 breaks through the relation microampere threshold B20 as a course signal fluctuation mutation region to obtain corresponding lower slide signal fluctuation data.
Preferably, the present invention further comprises the following method:
s4, counting the landing data of the historical airplane to obtain a plurality of microampere curve graphs A, calculating a historical microampere mean curve A according to all the microampere curve graphs A, and performing course signal fluctuation mutation analysis on the microampere curve graphs A to be analyzed based on the historical microampere mean curve A to obtain course signal abnormal fluctuation data.
Preferably, the present invention also includes the following method:
s5, counting the landing data of the historical airplane to obtain a plurality of microampere curve graphs B, calculating a historical microampere mean curve B according to all the microampere curve graphs B, and analyzing the microampere curve graphs B to be analyzed for glide slope signal fluctuation mutation to obtain glide slope signal abnormal fluctuation data based on the historical microampere mean curve B.
Preferably, the method for calculating the historical microampere mean curve a in step S4 of the method for analyzing and diagnosing the instrument landing system signal of the present invention is as follows: calculating the mean value of all points in the minimum unit, eliminating bad points according to the standard deviation, fitting the rest points in the minimum unit according to a least square method, and calculating a fitting linear relation; and calculating starting and stopping end points of a polyline in the minimum unit according to the fitted linear relation, performing thinning processing on all data in the minimum unit by using a centroid characteristic value method, and performing polyline drawing on the processed data to obtain a historical microampere mean curve A.
Preferably, the present invention further comprises the following method:
and S6, constructing a GIS geographic information map system, and performing combined, overlapped and display on the GIS geographic information map system according to longitude and latitude data, altitude data, course signal fluctuation data and glidepath signal fluctuation data in the airplane.
Preferably, the present invention further comprises the following method:
s7, an event analysis and prediction model is established, a course signal event training model and a glideslope signal event training model are established in the event analysis and prediction model, the course signal event training model comprises attribute information of course signal events and corresponding course signal fluctuation data, and the glideslope signal event training model comprises attribute information of the glideslope signal events and corresponding glideslope signal fluctuation data.
In a second aspect, the present invention provides an instrument landing system signal analysis and diagnosis apparatus, including:
the acquisition module is used for acquiring DDM indicating data of a course, DDM indicating data of a glidepath, longitude and latitude data and height data in the airplane;
the first microampere curve drawing module is used for constructing a course microampere fluctuation coordinate system taking the distance from a course platform and the deviation pointer driving current as horizontal and vertical coordinates, and drawing a course nominal microampere line, a course microampere boundary line and a microampere curve chart A;
the second microampere curve drawing module is used for constructing a lower slideway microampere wave coordinate system which takes the horizontal distance from the runway entrance and the deviation pointer driving current as horizontal and vertical coordinates, and drawing a nominal microampere line of the lower slideway, a microampere boundary line of the lower slideway and a microampere curve chart B;
the first calculation module is used for calculating and finding a course signal fluctuation mutation area in a course microampere fluctuation coordinate system and obtaining course signal fluctuation data;
and the second calculation module is used for calculating and finding out a fluctuation mutation area of the glide-slope signal in the glide-slope microampere fluctuation coordinate system and obtaining glide-slope signal fluctuation data.
In a third aspect, the present invention provides an electronic device, where the electronic device includes a data storage layer, a data processing layer and a terminal access layer, where the data storage layer is used to store data including a navigation database, a QAR database, a DAR database and an operation model parameter database, the data processing layer is used to store and execute a computer program to implement steps of an instrument landing system signal analysis and diagnosis method, and the terminal access layer is used to control terminal access and authority communication according to authority authentication.
Compared with the prior art, the invention has the following advantages and beneficial effects:
(1) The invention provides a full-coverage instrument landing system signal analysis and diagnosis method, a full-coverage instrument landing system signal analysis and diagnosis device and electronic equipment, which can realize the tracing of the time, the position and the signal structure change of a single event; the occurrence rule of the event can be found through statistical analysis, and the hidden operation danger can be found through analyzing the operation conditions of the preorder flight and the postorder flight or the conditions of a specific time period and a specific airspace; the method can analyze the signal trend change of the instrument landing system through big data, assist in judging the instrument landing operation condition, provide means for the operation monitoring of the instrument landing system, enhance the daily monitoring capability of an operation unit on ILS space signals, provide support for subsequent flight verification decision and improve the safety operation guarantee capability of a navigation system.
(2) The monitoring level of an ILS (intelligent lead station) by a manager and the investigation capability of similar abnormal events are comprehensively improved, the signal jitter characteristic curve of a specific flight can be graphically displayed, and a richer and more intuitive data analysis tool is provided for a management department; the method is beneficial to breaking through regional limitation, realizing remote supervision, improving the supervision capability of an industrial supervision department on the signal operation of the airport instrument landing system, conforming to the new technology provided by the industry, perfecting a civil aviation modern management system, and improving the modern management capability.
Drawings
FIG. 1 is a schematic flow diagram of the process of the present invention;
FIG. 2 is a schematic diagram of a course indication in an embodiment of the present invention;
FIG. 3 is a schematic diagram of microampere plot A in an embodiment of the present invention;
FIG. 4 is a schematic illustration of a glideslope indication in an embodiment of the present invention;
FIG. 5 is a schematic diagram of microampere plot B in an embodiment of the present invention;
FIG. 6 is a schematic diagram illustrating a GIS geographic information map system according to an embodiment of the present invention;
FIG. 7 is a system architecture diagram of an apparatus in an embodiment of the invention;
FIG. 8 is a diagram illustrating the course indicating data analyzed based on history according to the present embodiment;
FIG. 9 is a schematic diagram of the embodiment analyzing the indication data of the glidepath based on history;
fig. 10 is a schematic structural block diagram of a signal analysis and diagnosis device of the instrument landing system in the present embodiment;
fig. 11 is a schematic diagram illustrating an example of a system deployment of the electronic device in the embodiment.
Detailed Description
The present invention will be described in further detail with reference to the following examples:
examples
As shown in fig. 1 to 11, a method for analyzing and diagnosing a signal of an instrument landing system includes:
s1, constructing a course deviation coordinate system taking the distance from a course platform and the vertical direction deviation of a course as horizontal and vertical coordinates, reading DDM indicating data and longitude and latitude data of the course in the airplane, and drawing the course indicating data in the course deviation coordinate system. Referring to fig. 2, the intersection point of the horizontal and vertical coordinates of the course deviation coordinate system is (0, -1.5), and the nominal course line of the course in the figure is a horizontal line with zero horizontal coordinate, which corresponds to the centerline of the runway. The course indicating boundary line in the figure corresponds to the course guiding signal boundary (including 35 degree included angle line and 210 m DDM linear range standard line at the end of the runway). The vertical direction deviation of the course (namely the deviation relative to the central line of the runway or the signal guide central line of the course) is obtained by calculating the DDM indicating data and the longitude and latitude data of the course, and the distance between the longitude and latitude data (including the longitude and latitude information recorded in the QAR data or the longitude and latitude information recorded in the GPS navigation positioning) and the course is calculated to obtain the distance from the course table, so that the indicating data of the course can be drawn in a deviation coordinate system of the course.
And constructing a course microampere wave coordinate system with the distance from a course table and the driving current of the deviation pointer as horizontal and vertical coordinates, referring to fig. 3, wherein the horizontal and vertical coordinate intersection point of the course microampere wave coordinate system is (0-40), drawing a course nominal microampere line and a course microampere boundary line of the aircraft landing on the course microampere wave coordinate system, reading course DDM indicating data and longitude and latitude data in the aircraft, and drawing a microampere curve chart A reflecting the deviation degree of the course in the course microampere wave coordinate system. The DDM indicator diagram of the course comprises 35-degree included angle lines, 10-degree included angle lines and 210-meter DDM linear range standard lines at the tail end of the runway, when a CDI pointer is on the 210-meter standard lines, the DDM is just a full deviation value +/-0.155, the slope of each standard line can be obtained through calculation of a trigonometric function algorithm, and accordingly a course microampere boundary line (a maximum boundary line corresponding to the 35-degree included angle lines) is drawn, the course microampere boundary line is the embodiment of a course guide signal coverage boundary in a course microampere wave coordinate system, and the course nominal microampere corresponds to microampere lines without deviation of the central line of the runway. The microampere (uA) value deviating from the pointer driving current (namely the driving current deviating from the central line of the runway and being the course driving current) is obtained through calculation of the DDM indicating data of the course, and the distance between the longitude and latitude data (including the longitude and latitude information recorded in QAR data or the longitude and latitude information recorded in GPS navigation positioning) and the course (the course longitude and latitude information) is calculated to obtain the distance from the course, so that a microampere curve graph A can be drawn in a course microampere wave coordinate system. As shown in FIG. 3, according to the microampere curve A in the microampere wave coordinate system of the course of this embodiment, it can be directly seen that the signal fluctuation amplitude is maximum within 10km, especially the signal fluctuation amplitude reaches the peak value at 5-6 km.
S2, constructing a glidepath deviation coordinate system taking the distance from the runway entrance and the corrected sea pressure height as horizontal and vertical coordinates, reading glidepath DDM indicating data, longitude and latitude data and height data in the airplane, and drawing the glidepath indicating data in the glidepath deviation coordinate system. Referring to fig. 4, the intersection point of the abscissa and the ordinate of the glidepath deviation coordinate system is (0, 157), the nominal trajectory line of the glidepath in the drawing is the center line of the glidepath guide signal covered in the glidepath deviation coordinate system, and the boundary line of the glidepath guide is the representation of the glidepath guide signal covered boundary in the glidepath deviation coordinate system. The corrected sea pressure height is obtained through calculation of DDM indicating data, longitude and latitude data and height data of the lower slideway, and the distance between the longitude and latitude data (including longitude and latitude information recorded in QAR data or longitude and latitude information recorded in GPS navigation positioning) and a runway entrance (the longitude and latitude information of the runway entrance) is calculated to obtain the distance from the runway entrance, so that a microampere curve graph A can be drawn in a course deviation coordinate system.
Constructing a glidepath microampere wave coordinate system which takes a horizontal distance from a runway entrance and a deviated pointer driving current as horizontal and vertical coordinates, and drawing a glidepath nominal microampere line and a glidepath microampere boundary line of the landing of the airplane on the glidepath microampere wave coordinate system, referring to fig. 4, wherein the horizontal and vertical coordinate intersection point of the glidepath microampere wave coordinate system is (0-40), the glidepath nominal microampere line in the drawing is a central line of a glidepath guide signal covered in the glidepath microampere wave coordinate system, and the glidepath microampere boundary line is the embodiment of the glidepath guide signal covered boundary in the glidepath microampere wave coordinate system. Drawing a microampere curve chart B reflecting the deviation degree of the glidepath in a glidepath microampere fluctuation coordinate system according to the glidepath indication data; calculating to obtain a deviation pointer driving current (which is a glide slope driving current) through the glide slope DDM indicating data, longitude and latitude data and height data, calculating to obtain a distance from a runway entrance through the distance between the longitude and latitude data (including longitude and latitude information recorded in QAR data or longitude and latitude information recorded in GPS navigation positioning) and the runway entrance (the longitude and latitude information of the runway entrance), drawing a microampere curve diagram B in a glide slope microampere wave coordinate system, and preliminarily diagnosing the deviation condition of the instrument landing system glide slope guiding signal through the matching degree and the deviation degree of the microampere curve diagram B and a nominal microampere line of the glide slope.
And S3, finding a course signal fluctuation mutation area in the microampere curve chart A in the course microampere fluctuation coordinate system and obtaining course signal fluctuation data. And finding out a lower slide deviation signal fluctuation mutation area in the microampere curve diagram B in the lower slide microampere fluctuation coordinate system and obtaining lower slide signal fluctuation data.
In some embodiments, in step S3, a deviation microampere threshold a10 of the microampere graph a and the nominal microampere line of the course is set, a deviation microampere value a11 of the microampere graph a and the nominal microampere line of the course is calculated, the deviation microampere value a11 is compared with the deviation microampere threshold a10, and a region where the deviation microampere value a11 exceeds the deviation microampere threshold a10 is used as a course signal fluctuation mutation region and corresponding course signal fluctuation data is obtained, so that the course signal fluctuation mutation region can be quickly identified and course signal fluctuation data of the mutation region can be obtained through calculation and comparison of the deviation microampere threshold a 10. Setting a relation microampere threshold A20 between the microampere graph A and a course microampere boundary line (the relation microampere threshold A20 is limited to the condition that a point on the microampere graph A does not break through the course microampere boundary line, if the point on the microampere graph A breaks through the course microampere boundary line, the point on the microampere graph A breaks through the relation microampere threshold A20 and is judged to be abnormal fluctuation signal data, under the condition that the point on the microampere graph A does not break through the course microampere boundary line, the relation microampere threshold A20 limits a distance threshold, if the distance exceeds the distance threshold, the point on the microampere graph A is judged to be abnormal fluctuation signal data), calculating a risk microampere distance value A21 between the microampere graph A and the course microampere boundary line (the risk microampere distance value A21 is the distance from the point on the microampere graph A20 to the course microampere boundary line), comparing the risk microampere distance value A21 with the relation microampere threshold A20, and obtaining the course microampere signal fluctuation data by taking the abrupt change area of the course microampere boundary line.
In some embodiments, in step S3, a deviation microampere threshold B10 of the microampere graph B and the nominal microampere line of the lower sliding track is set, a deviation microampere value B11 of the microampere graph B and the nominal microampere line of the lower sliding track is calculated, the deviation microampere value B11 is compared with the deviation microampere threshold B10, a region where the deviation microampere value B11 exceeds the deviation microampere threshold B10 is used as a sudden change region of the fluctuation of the lower sliding track signal and corresponding fluctuation data of the lower sliding track signal are obtained, so that the sudden change region of the fluctuation of the lower sliding track signal can be quickly identified and the fluctuation data of the lower sliding track signal of the sudden change region can be obtained through calculation and comparison of the deviation microampere threshold B10. Setting a relation microampere threshold B20 between the microampere graph B and a lower slide microampere boundary line (the relation microampere threshold B20 is limited to the condition that a point on the microampere graph B does not break through the lower slide microampere boundary line, if the point on the microampere graph B breaks through the lower slide microampere boundary line, the point on the microampere graph B is considered to break through the relation microampere threshold B20 and is judged to be abnormal fluctuation signal data, under the condition that the point on the microampere graph B does not break through the lower slide microampere boundary line, the relation microampere threshold B20 limits a distance threshold, if the distance exceeds the distance threshold, the point on the microampere graph B is judged to be abnormal fluctuation signal data), calculating a risk microampere distance value B21 between the microampere graph B and the lower slide microampere boundary line (the risk microampere distance value B21 is the distance from the point on the microampere graph B to the lower slide microampere boundary line), comparing the risk microampere distance value B21 with the relation microampere threshold B20, and taking the area of the risk microampere distance value B21 breaking through the microampere threshold B20 as a sudden change area of the corresponding lower slide signal as a sudden change area and obtaining the corresponding lower slide.
In some embodiments, the invention also includes methods of:
s4, counting the landing data of the historical airplane to obtain a plurality of microampere curve graphs A, calculating a historical microampere mean curve A according to all the microampere curve graphs A, and performing course signal fluctuation mutation analysis on the microampere curve graphs A to be analyzed based on the historical microampere mean curve A to obtain course signal abnormal fluctuation data. FIG. 8 illustrates a course indicating data obtained by statistics of landing data of a historical airplane, wherein all flight data in a start-stop time period are counted by selecting an airport, a runway and start-stop time, grouping display is performed according to dates, mean value statistics calculation is performed on DDM data of all groups, historical course indicating mean value data is drawn, because QAR data is batch point data and sampling frequency is consistent and sampling time is inconsistent, a mean value curve needs to be calculated through a scientific algorithm (such as variance), specific accidental factors can be eliminated through the mean value curve, signal curve trend in unit time is analyzed, meanwhile, superposition of multiple groups of data curves is supported, comparative analysis is performed in the graph, and signal fluctuation development trend is judged. And similarly, further obtaining a historical microampere mean curve A in the course microampere fluctuating coordinate system.
In some embodiments, the historical microampere mean curve a in step S4 is calculated as follows: calculating the mean value of all points in the minimum unit, eliminating bad points according to the standard deviation, fitting the rest points in the minimum unit according to a least square method, and calculating a fitting linear relation; and calculating start and stop end points of a polyline in the minimum unit according to the fitted linear relation, performing thinning processing on all data in the minimum unit by using a centroid characteristic value method, and performing polyline drawing on the processed data to obtain a historical microampere mean curve A.
In some embodiments, the invention also includes methods of:
s5, counting the landing data of the historical airplane to obtain a plurality of microampere curve graphs B, calculating a historical microampere mean curve B according to all the microampere curve graphs B, and analyzing the microampere curve graphs B to be analyzed for the fluctuation and sudden change of the glide slope signals based on the historical microampere mean curve B to obtain the abnormal fluctuation data of the glide slope signals. Fig. 8 illustrates, for example, glidepath indication data obtained by statistics of historical landing data of an aircraft, and all flight data within a start-stop time period are counted by selecting an airport, a runway, and start-stop time, and are displayed in groups by date. Carrying out mean value statistical calculation on DDM data of all the groups, and drawing historical down-runner indication mean value data; the same course direction diagram calculates a mean curve through a scientific algorithm (such as variance), specific accidental factors can be eliminated through the mean curve, the signal curve trend in unit time is analyzed, meanwhile, the method supports superposition of multiple groups of data curves, comparative analysis is carried out in the diagram, and the signal fluctuation development trend is judged. And similarly, further obtaining a historical microampere mean curve B in the glide slope microampere fluctuating coordinate system.
In some embodiments, the invention also includes methods of:
s6, constructing a GIS geographic information map system, and performing combined, overlapped and display on the GIS geographic information map system according to longitude and latitude data, altitude data, course signal fluctuation data and glidepath signal fluctuation data in the airplane. The GIS geographic information map system is used for combined display, track position information is calculated and drawn through geographic space, meanwhile, the platform supports three-dimensional track space display, flight display is simulated, navigation elements are comprehensively overlapped and displayed, flight track reappearance of events can be achieved, and analysis and diagnosis can be carried out more visually and conveniently.
In some embodiments, the invention further includes methods of:
s7, an event analysis and prediction model is built, a course signal event training model and a lower sliding path signal event training model are built in the event analysis and prediction model, the course signal event training model comprises the attribute information of a course signal event and corresponding course signal fluctuation data, and the lower sliding path signal event training model comprises the attribute information of the lower sliding path signal event and corresponding lower sliding path signal fluctuation data. The event analysis prediction model is accessed into an AI intelligent learning algorithm, analysis prediction is carried out according to historical big data, the similarity between a current data scene and a historical data scene is judged according to the incidence relation between data characteristics determined by a historical data set and the influence factors of signal fluctuation and the combination of wider scene data factors, and therefore the future development trend of the feedback signal is predicted.
An instrument landing system signal analysis and diagnosis device, referring to fig. 10, includes an acquisition module, a first microampere curve drawing module, a second microampere curve drawing module, a first calculation module, and a second calculation module:
the acquisition module is used for acquiring course DDM indicating data, glidepath DDM indicating data, longitude and latitude data and height data in the airplane. The embodiment is based on the WQAR big data of the 52-family airline airplanes collected by the local base station, is synchronous with the flight data of the airline, comprises QAR and DAR data types, has the basic data for performing performance analysis on all ILS equipment, and builds the remote signal analysis and diagnosis device of the instrument landing system based on the data. In order to more accurately analyze signals and diagnose faults of the instrument landing system, the device can also perform fusion of multi-source data such as navigation data, airport equipment data and the like, reproduce flight trajectories of aircrafts and relevant states of the instrument landing system, and realize quantitative technical analysis of space signals of the instrument landing system.
The first microampere curve drawing module is used for constructing a course microampere fluctuation coordinate system taking the distance from a course platform and the deviation of the pointer driving current as horizontal and vertical coordinates, and drawing a course nominal microampere line, a course microampere boundary line and a microampere curve chart A; the first microampere curve drawing module of this embodiment may directly perform the following calculation (which may also be implemented by the first calculation module): the microampere (uA) value deviating from the pointer driving current (namely the driving current deviating from the central line of the runway and being the course driving current) is obtained through calculation of the DDM indicating data of the course, and the distance between the longitude and latitude data (including the longitude and latitude information recorded in QAR data or the longitude and latitude information recorded in GPS navigation positioning) and the course (the course longitude and latitude information) is calculated to obtain the distance from the course, so that a microampere curve graph A can be drawn in a course microampere wave coordinate system.
The second microampere curve drawing module is used for constructing a lower slideway microampere wave coordinate system which takes the horizontal distance from the runway entrance and the deviation pointer driving current as horizontal and vertical coordinates, and drawing a nominal microampere line of the lower slideway, a microampere boundary line of the lower slideway and a microampere curve chart B; the second microampere curve drawing module of this embodiment may directly perform the following calculation (or may be implemented by the second calculation module): calculating to obtain a deviation pointer driving current (which is a glide-slope driving current) through glide-slope DDM indicating data, longitude and latitude data and height data, and calculating to obtain a distance from a runway entrance (longitude and latitude information of the runway entrance) through distance between the longitude and latitude data (including longitude and latitude information recorded in QAR data or longitude and latitude information recorded in GPS navigation positioning) and the runway entrance, thereby drawing a microampere curve chart B in a glide-slope microampere wave coordinate system.
The first calculation module is used for calculating and finding out a course signal fluctuation mutation area in a course microampere fluctuation coordinate system and obtaining course signal fluctuation data.
And the second calculation module is used for calculating and finding out a glide-slope signal fluctuation mutation area in the glide-slope microampere fluctuation coordinate system and obtaining glide-slope signal fluctuation data.
An electronic device comprises a data storage layer, a data processing layer and a terminal access layer which are communicated with each other, wherein the data storage layer is used for storing data including a navigation database, a QAR database, a DAR database and an operation model parameter database, referring to fig. 7, and the data storage layer is respectively used for correspondingly storing the navigation data, the QAR data, the DAR data and the operation model parameters. As shown in fig. 7, the data processing layer (which is the core of the electronic device of the present invention) includes an application service layer and a business implementation layer, the application service layer mainly adopts a service-oriented architecture design, realizes effective integration and management of services through a unified enterprise-level bus, and quickly builds a function of a related module based on the application service, and the business implementation layer realizes quick building of the related business module through the application service layer. The terminal access layer is used for controlling terminal access and authority communication according to authority authentication so as to control and realize the authority and the use requirements of different users. Preferably, in this embodiment, referring to fig. 11, software and hardware in this embodiment are mainly deployed in a data center, an airport, a local management office, and other users, without installing a client, a B/S framework can implement online access through a browser, and access to a webapi service interface published by the data center is implemented in a user authorization manner through a civil aviation communication network or a private line, so as to implement business function operations.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. A method for analyzing and diagnosing instrument landing system signals is characterized by comprising the following steps: the method comprises the following steps:
s1, constructing a course microampere fluctuation coordinate system taking a distance from a course platform and a deviation pointer driving current as horizontal and vertical coordinates, drawing a course nominal microampere line and a course microampere boundary line of aircraft landing on the course microampere fluctuation coordinate system, reading course DDM indicating data and longitude and latitude data in the aircraft, and drawing a microampere curve chart A reflecting the deviation degree of the course in the course microampere fluctuation coordinate system;
s2, constructing a glidepath deviation coordinate system with the distance from a runway entrance and the corrected sea pressure height as horizontal and vertical coordinates, reading glidepath DDM indicating data, longitude and latitude data and height data in the airplane, and drawing glidepath indicating data in the glidepath deviation coordinate system; constructing a glidepath microampere fluctuation coordinate system taking the horizontal distance from a runway entrance and the driving current of a deviation pointer as horizontal and vertical coordinates, drawing a glidepath nominal microampere line and a glidepath microampere boundary line of the airplane landing on the glidepath microampere fluctuation coordinate system, and drawing a microampere curve chart B reflecting the deviation degree of the glidepath in the glidepath microampere fluctuation coordinate system according to glidepath indication data;
s3, finding a course signal fluctuation mutation area in the microampere curve chart A in the course microampere fluctuation coordinate system and obtaining course signal fluctuation data; finding out the fluctuation mutation area of the glide slope signal in the microampere curve chart B in the glide slope microampere fluctuation coordinate system and obtaining glide slope signal fluctuation data.
2. The method of claim 1, wherein: in the step S3, a deviation microampere threshold value A10 of the microampere graph A and a nominal microampere line of the course is set, a deviation microampere value A11 of the microampere graph A and the nominal microampere line of the course is calculated, the deviation microampere value A11 is compared with the deviation microampere threshold value A10, and an area, exceeding the deviation microampere threshold value A10, of the deviation microampere value A11 is used as a signal fluctuation mutation area of the course to obtain corresponding signal fluctuation data of the course; setting a relation microampere threshold A20 between the microampere curve chart A and a course microampere boundary line, calculating a risk microampere distance value A21 of the microampere curve chart A and the course microampere boundary line, comparing the risk microampere distance value A21 with the relation microampere threshold A20, and taking a region where the risk microampere distance value A21 breaks through the relation microampere threshold A20 as a course signal fluctuation mutation region to obtain corresponding course signal fluctuation data.
3. The method of claim 1, wherein: in step S3, a deviation microampere threshold B10 of the microampere graph B and the nominal microampere line of the lower runner is set, a deviation microampere value B11 of the microampere graph B and the nominal microampere line of the lower runner is calculated, the deviation microampere value B11 is compared with the deviation microampere threshold B10, and a region where the deviation microampere value B11 exceeds the deviation microampere threshold B10 is used as a fluctuation abrupt change region of the lower runner signal and corresponding fluctuation data of the lower runner signal is obtained; setting a relation microampere threshold B20 between the microampere curve chart B and a lower slide microampere boundary line, calculating a risk microampere distance value B21 of the microampere curve chart B and the lower slide microampere boundary line, comparing the risk microampere distance value B21 with the relation microampere threshold B20, and taking a region where the risk microampere distance value B21 breaks through the relation microampere threshold B20 as a course signal fluctuation mutation region to obtain corresponding lower slide signal fluctuation data.
4. The method of claim 1, wherein: the method also comprises the following steps:
s4, counting the landing data of the historical airplane to obtain a plurality of microampere curve graphs A, calculating a historical microampere mean curve A according to all the microampere curve graphs A, and performing course signal fluctuation mutation analysis on the microampere curve graphs A to be analyzed based on the historical microampere mean curve A to obtain course signal abnormal fluctuation data.
5. The method of claim 1, wherein: the method also comprises the following steps:
s5, counting the landing data of the historical airplane to obtain a plurality of microampere curve graphs B, calculating a historical microampere mean curve B according to all the microampere curve graphs B, and analyzing the microampere curve graphs B to be analyzed for glide slope signal fluctuation mutation to obtain glide slope signal abnormal fluctuation data based on the historical microampere mean curve B.
6. The method of claim 4, wherein: the method for calculating the historical microampere mean curve A in the step S4 comprises the following steps: calculating the mean value of all points in the minimum unit, eliminating bad points according to the standard deviation, fitting the rest points in the minimum unit according to a least square method, and calculating a fitting linear relation; and calculating starting and stopping end points of a polyline in the minimum unit according to the fitted linear relation, performing thinning processing on all data in the minimum unit by using a centroid characteristic value method, and performing polyline drawing on the processed data to obtain a historical microampere mean curve A.
7. The method of claim 4, wherein: the method also comprises the following steps:
s6, constructing a GIS geographic information map system, and performing combined, overlapped and display on the GIS geographic information map system according to longitude and latitude data, altitude data, course signal fluctuation data and glidepath signal fluctuation data in the airplane.
8. The method of claim 7, wherein: the method also comprises the following steps:
s7, an event analysis and prediction model is established, a course signal event training model and a glideslope signal event training model are established in the event analysis and prediction model, the course signal event training model comprises attribute information of course signal events and corresponding course signal fluctuation data, and the glideslope signal event training model comprises attribute information of the glideslope signal events and corresponding glideslope signal fluctuation data.
9. A signal analysis and diagnosis device for an instrument landing system is characterized in that: the method comprises the following steps:
the acquisition module is used for acquiring DDM indicating data of a course, DDM indicating data of a glidepath, longitude and latitude data and height data in the airplane;
the first microampere curve drawing module is used for constructing a course microampere fluctuation coordinate system taking the distance from a course platform and the deviation of the pointer driving current as horizontal and vertical coordinates, and drawing a course nominal microampere line, a course microampere boundary line and a microampere curve chart A;
the second microampere curve drawing module is used for constructing a lower slideway microampere wave coordinate system which takes the horizontal distance from the runway entrance and the deviating pointer driving current as horizontal and vertical coordinates, and drawing a lower slideway nominal microampere line, a lower slideway microampere boundary line and a microampere curve chart B;
the first calculation module is used for calculating and finding a course signal fluctuation mutation area in a course microampere fluctuation coordinate system and obtaining course signal fluctuation data;
and the second calculation module is used for calculating and finding out a fluctuation mutation area of the glide-slope signal in the glide-slope microampere fluctuation coordinate system and obtaining glide-slope signal fluctuation data.
10. An electronic device, characterized in that: the electronic equipment comprises a data storage layer, a data processing layer and a terminal access layer which are communicated with each other, wherein the data storage layer is used for storing data comprising a navigation database, a QAR database, a DAR database and an operation model parameter database, the data processing layer is used for storing and executing computer programs and realizing the steps of the instrument landing system signal analysis and diagnosis method of any one of claims 1-8, and the terminal access layer is used for controlling terminal access and authority communication according to authority authentication.
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| CN113205706A (en) * | 2021-04-22 | 2021-08-03 | 九州云(北京)科技发展有限公司 | ILS signal quality monitoring method based on flight QAR data |
| CN114047778A (en) * | 2021-10-21 | 2022-02-15 | 哈尔滨工程大学 | Small airplane short-distance automatic landing transverse and lateral control method |
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| JP2002092799A (en) * | 2000-09-19 | 2002-03-29 | Toshiba Corp | Landing guide diagnosing system |
| CN111880569A (en) * | 2020-08-04 | 2020-11-03 | 北京航空航天大学 | Ground station display system and method for guiding check unmanned aerial vehicle to approach landing |
| CN113205706A (en) * | 2021-04-22 | 2021-08-03 | 九州云(北京)科技发展有限公司 | ILS signal quality monitoring method based on flight QAR data |
| CN114047778A (en) * | 2021-10-21 | 2022-02-15 | 哈尔滨工程大学 | Small airplane short-distance automatic landing transverse and lateral control method |
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