CN117008632A - Course track deviation signal monitoring voting method, device and storage medium - Google Patents
Course track deviation signal monitoring voting method, device and storage medium Download PDFInfo
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Abstract
The application discloses a course deviation signal monitoring voting method, a device and a storage medium, wherein the method comprises the following steps: generating an analytic redundancy signal according to flight data of the aircraft; generating an initial hardware redundancy signal according to the data acquired by the redundancy sensor; filtering the initial hardware redundancy signal based on the analytical redundancy signal to generate a hardware redundancy signal; and carrying out monitoring voting on the hardware redundancy signal and the analysis redundancy signal to obtain a course deviation value, and controlling the flight state of the aircraft according to the course deviation value. The technical scheme provided by the application can solve the technical problem that the reliability of signals acquired by the redundancy sensor is low in the prior art, so that equipment faults cannot be accurately detected when the course deviation signal is monitored and voted.
Description
Technical Field
The application relates to the technical field of aircraft control, in particular to a course deviation signal monitoring voting method, a device and a storage medium.
Background
For modern large civil airliners, the course deviation (LOC) and the glideslope deviation signal (GS) issued by the Instrumentation Landing System (ILS) are typically used in automatic landing. In general, the instrument landing system signal of a modern large civil airliner is double redundancy, and LOC deviation and GS deviation signals are easily influenced by moving objects such as ground automobiles and airplanes when the airplanes automatically land, so that high-frequency noise exists in the LOC deviation and GS deviation signals sent by ILS, the deviation signals of a course and a glide slope after monitoring voting are further separated from the true values, and the automatic landing function is seriously lost.
In order to meet the requirements of high safety and high reliability of flight, most civil airliners adopt redundant hardware redundancy, a plurality of sets of sensors are configured, but the method faces some technical problems, and when the hardware redundancy signals acquired by the plurality of sets of sensors are voted, a voting algorithm mainly adopts a median voting method, an arithmetic average voting method, a majority coincidence voting method and the like for the hardware redundancy signals. For dual redundancy signals, the redundancy signals are typically differenced to determine if the signals are identical. On one hand, the data processing object of the algorithm only has hardware redundancy signals acquired by the sensor, and the signal type is single; on the other hand, the voting method does not judge the fault condition of the sensor, if one or more sensors are in a problem, accurate data are difficult to obtain, the voting result is inaccurate, the accuracy of the obtained course deviation signal is low, and the safety requirement is difficult to meet.
Disclosure of Invention
The application provides a method, a device and a storage medium for monitoring and voting course deviation signals, which aim to effectively solve the technical problem that in the prior art, the reliability of signals acquired by redundancy sensors is low, so that equipment faults cannot be accurately detected when the course deviation signals are monitored and voted.
According to one aspect of the application, the application provides a course deviation signal monitoring voting method, which comprises the following steps:
generating an analytic redundancy signal according to flight data of the aircraft;
generating an initial hardware redundancy signal according to the data acquired by the redundancy sensor;
filtering the initial hardware redundancy signal based on the analytical redundancy signal to generate a hardware redundancy signal;
and judging the working state of the redundancy sensor according to the hardware redundancy signal, if the redundancy sensor fails, carrying out monitoring voting on the hardware redundancy signal and the analysis redundancy signal to obtain a course deviation value, and controlling the flight state of the aircraft according to the course deviation value.
Further, the generating the resolution residual signal according to the flight data of the aircraft includes:
acquiring the latest course deviation value from the historical data;
acquiring the flight data, wherein the flight data is one or more of aircraft inertial navigation data, aircraft position information and channel position information;
and performing object understanding calculation on the flight state of the aircraft based on the latest course deviation value and the flight data to generate the resolution residual signal.
Further, the generating the initial hardware redundancy signal according to the data acquired by the redundancy sensor includes:
acquiring a first wireless signal transmitted by a first redundancy sensor and a received first echo signal, and generating a first initial hardware redundancy signal according to the first wireless signal and the first echo signal;
and acquiring a second wireless signal transmitted by a second redundancy sensor and a second received echo signal, and generating a second initial hardware redundancy signal according to the second wireless signal and the second echo signal.
Further, the filtering the initial hardware redundancy signal based on the analytical redundancy signal to generate a hardware redundancy signal includes:
and respectively carrying out Kalman filtering on the first initial hardware redundancy signal and the second initial hardware redundancy signal based on the analysis redundancy signal so as to generate a first hardware redundancy signal and a second hardware redundancy signal.
Further, the judging the working state of the redundancy sensor according to the hardware redundancy signal includes:
calculating a first signal difference between the first hardware redundancy signal and the second hardware redundancy signal;
if the first signal difference value is smaller than a preset signal threshold value, determining that the redundancy sensor is in a normal state;
and if the first signal difference value is greater than or equal to the signal threshold value, acquiring a plurality of historical first signal difference values in a preset quantity or preset time in the historical data, and determining the working state of the redundancy sensor according to the first signal difference value and the historical first signal difference value.
Further, the determining the working state of the redundancy sensor according to the first signal difference value and the historical first signal difference value includes:
if the preset number of the historical first signal differences are all larger than or equal to the signal threshold value, determining that the redundancy sensor is in a continuous fault state, otherwise, determining that the redundancy sensor is in an instantaneous fault state; or alternatively, the first and second heat exchangers may be,
calculating a state parameter from a plurality of differences in the first signal difference and the historical first signal difference; wherein, when the difference value is greater than or equal to the signal threshold value, the value of the state parameter is increased by m; when the difference value is smaller than the signal threshold value, the value of the state parameter is reduced by n; and if the state parameter is greater than or equal to a preset parameter threshold, determining that the redundancy sensor is in a continuous fault state, otherwise, determining that the redundancy sensor is in an instantaneous fault state.
Further, the monitoring voting on the hardware redundancy signal and the analysis redundancy signal to obtain a course deviation value includes:
and if the redundancy sensor is in a normal state, performing average value taking operation on the first hardware redundancy signal and the second hardware redundancy signal to obtain the heading channel deviation value.
Further, the monitoring voting on the hardware redundancy signal and the analysis redundancy signal to obtain a course deviation value includes:
and if the redundancy sensor is in a continuous fault state, determining the course deviation value according to the analysis redundancy signal.
Further, the monitoring voting on the hardware redundancy signal and the analysis redundancy signal to obtain a course deviation value includes:
if the redundancy sensor is in an instantaneous fault state, calculating a second signal difference value between the analysis redundancy signal and the first hardware redundancy signal;
calculating a second signal difference between the analytical redundancy signal and the first hardware redundancy signal;
calculating a third signal difference between the analytical redundancy signal and the second hardware redundancy signal;
calculating a mean value signal of the first hardware redundancy signal and the second hardware redundancy signal, and calculating a fourth signal difference value between the analysis redundancy signal and the mean value signal;
if the second signal difference value is smaller than the signal threshold value, determining that the second redundancy sensor is in an instantaneous fault state, and determining the heading channel deviation value according to the first hardware redundancy signal;
if the third signal difference value is smaller than the signal threshold value, determining that the first redundancy sensor is in an instantaneous fault state, and determining the heading channel deviation value according to the second hardware redundancy signal;
if the fourth signal difference value is smaller than the signal threshold value, determining that the first redundancy sensor and the second redundancy sensor are in an instantaneous fault state, and determining the heading channel deviation value according to the analysis redundancy signal;
and if the second signal difference value, the third signal difference value and the fourth signal difference value are all larger than or equal to the signal threshold value, acquiring the latest course deviation value from the historical data as the course deviation value.
According to another aspect of the present application, there is also provided a course deviation signal monitoring voting apparatus, the apparatus comprising:
the analysis module is used for generating an analysis redundancy signal according to the flight data of the aircraft;
the data acquisition module is used for generating an initial hardware redundancy signal according to the data acquired by the redundancy sensor;
the filtering module is used for filtering the initial hardware redundancy signal based on the analysis redundancy signal to generate a hardware redundancy signal;
and the voting module is used for judging the working state of the redundancy sensor according to the hardware redundancy signal, monitoring and voting the hardware redundancy signal and the analysis redundancy signal to obtain a course deviation value when the redundancy sensor fails, and controlling the flight state of the aircraft according to the course deviation value.
According to another aspect of the present application there is also provided a storage medium having stored therein a plurality of instructions adapted to be loaded by a processor to perform any of the course deviation signal monitoring voting methods described above.
Through one or more of the above embodiments of the present application, at least the following technical effects can be achieved:
in the technical scheme disclosed by the application, the flight data is resolved to obtain the analytic redundancy signal, the initial hardware redundancy signal is obtained, the hardware redundancy signal is obtained through filtering of the analytic redundancy signal, and the hardware redundancy signal and the analytic redundancy signal are monitored and voted to obtain the course deviation value. The method and the device are based on virtual sensor technology analysis to obtain the signal analysis redundancy signal, and on the basis of not adding additional equipment, the physical analysis relation among the signals is utilized to analyze to obtain the course way signal of the automatic landing system, so that the number of sensors is reduced, and wiring is facilitated. Redundancy monitoring voting is carried out by analyzing redundancy signals such as the redundancy signals and the hardware redundancy signals to serve as an important basis for detecting whether the hardware redundancy signals have faults or not, so that fault signals are accurately isolated, and the voting signals are closer to a true value. In addition, the smooth high-precision analysis redundancy signal is utilized to filter the initial hardware redundancy signal, noise signals are removed through signal fault detection and isolation, and the reliability of the automatic landing system is improved.
In summary, the method introduces the analysis redundancy course deviation signal, on one hand, utilizes the analysis redundancy course deviation to filter noise signals in the course deviation signal output by the instrument landing equipment, and on the other hand, constructs a three-redundancy monitoring voting framework according to different characteristics of the signals, so that isolation fault signals can be effectively detected, and the integrity and usability of the course deviation signal are improved.
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The technical solution and other advantageous effects of the present application will be made apparent by the following detailed description of the specific embodiments of the present application with reference to the accompanying drawings.
FIG. 1 is a flow chart of steps of a method for monitoring and voting for course deviation signals according to an embodiment of the present application;
FIG. 2 is a schematic diagram of an initial hardware redundancy signal;
FIG. 3 is a schematic diagram of signal monitoring voting according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a device for monitoring and voting course deviation signals according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. It will be apparent that the described embodiments are only some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In the description of the present application, it should be noted that, unless explicitly specified and defined otherwise, the term "and/or" herein is merely an association relationship describing associated objects, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. The character "/" herein generally indicates that the associated object is an "or" relationship unless otherwise specified.
FIG. 1 is a flowchart illustrating steps of a method for monitoring and voting for a course deviation signal according to an embodiment of the present application, where according to an aspect of the present application, the method includes:
step 101: generating an analytic redundancy signal according to flight data of the aircraft;
step 102: generating an initial hardware redundancy signal according to the data acquired by the redundancy sensor;
step 103: filtering the initial hardware redundancy signal based on the analytical redundancy signal to generate a hardware redundancy signal;
step 104: and judging the working state of the redundancy sensor according to the hardware redundancy signal, if the redundancy sensor fails, carrying out monitoring voting on the hardware redundancy signal and the analysis redundancy signal to obtain a course deviation value, and controlling the flight state of the aircraft according to the course deviation value.
Voting the redundancy data to obtain a course deviation value, namely calculating the angle value of the plane deviated from the central line in a plurality of modes, determining a final course deviation value according to a voting method, and adjusting the flight direction of the plane by using the course deviation value to enable the plane to land on the runway along the central line of the runway. The scheme is based on the mixed redundancy monitoring voting of the signals analyzed by the virtual sensor technology and the two hardware redundancy signals. The analyzed signals are used as important basis for detecting whether the hardware redundancy signals have faults or not, so that the fault signals are accurately isolated, and the voting signals are closer to the true value; on the other hand, the smooth high-precision analysis course deviation signal obtained by analysis and the course deviation signal output by the machine are utilized for filtering so as to filter noise signals in the sensor signals.
The above steps 101 to 104 are specifically described below.
In step 101, a resolution signal is generated from flight data of the aircraft.
The signals in the scheme are specifically course deviation signals, and the three redundancy signals are respectively an analysis redundancy signal and two hardware redundancy signals which are used for representing course deviation, wherein the analysis redundancy signals are virtual redundancy signals obtained through data analysis and can also be converted into calculation redundancy signals, and the signals are not obtained according to redundancy sensors, but are calculated according to inertial navigation flight data, GPS data and channel data on an airplane.
In step 102, an initial hardware redundancy signal is generated from data acquired by a redundancy sensor.
Illustratively, the redundancy sensor is an on-board instrument landing device, and a plurality of redundancy sensors, such as two redundancy sensors and three redundancy sensors, i.e., two or three sets of mutually independent sensor systems, are provided on the aircraft, each of which may be different in configuration and model, but identical in function and function, all of which are used to obtain the same target data. For example, two independent sets of redundancy sensors are used to obtain course bias. The aircraft is provided with a plurality of independent redundancy sensors, so that the reliability of data is improved, the safety of the aircraft is ensured, and the accurate data of the final control aircraft is obtained by comparing and analyzing two or more groups of data. If one set of sensors fails, control data can be obtained according to the data of the other set of sensors.
In the scheme, the two groups of initial hardware redundancy signals are received according to the two redundancy instrument landing equipment, so that the accuracy of data can be ensured to a certain extent, and the problems of complex wiring and maintenance and the like caused by too many sensors are prevented.
In step 103, the initial hardware redundancy signal is filtered based on the analytical redundancy signal to generate a hardware redundancy signal.
Illustratively, FIG. 2 is a schematic diagram of an initial hardware redundancy signal, as shown, the signal with amplitude ranging from 0-0.03 is Left-LOC, and the signal with amplitude ranging from 0-0.4 is Right-LOC, i.e. the data obtained by two sets of redundancy sensors on the Left and Right sides of the aircraft. As shown in the figure, LOC deviation signals are easily affected by moving objects such as ground automobiles, airplanes and the like when the airplane automatically lands, so that high-frequency noise exists in the signals.
However, the data of the analysis redundancy signal is relatively stable and is less influenced by external factors, so that the analysis redundancy signal can be used for eliminating noise in the initial hardware redundancy signal, and a relatively smooth hardware redundancy signal is obtained.
In step 104, the working state of the redundancy sensor is determined according to the hardware redundancy signal, if the redundancy sensor fails, the hardware redundancy signal and the analysis redundancy signal are monitored and voted to obtain a course deviation value, and the flight state of the aircraft is controlled according to the course deviation value.
Illustratively, this step is a specific monitoring voting process, and multiple judgments are specifically required according to three redundancy signals, so as to obtain the most accurate voting result.
Further, the generating the resolution residual signal according to the flight data of the aircraft includes:
acquiring the latest course deviation value from the historical data;
acquiring the flight data, wherein the flight data is one or more of aircraft inertial navigation data, aircraft position information and channel position information;
and performing object understanding calculation on the flight state of the aircraft based on the latest course deviation value and the flight data to generate the resolution residual signal.
For example, in the process of monitoring and voting of the aircraft, historical data is saved, including a course deviation value obtained after each voting, a fault condition of each redundancy sensor and the like. The course deviation value obtained after the last voting is used for controlling the current flight state of the aircraft, so that the data are required to be acquired to participate in data calculation so as to improve the calculation accuracy, and the latest course deviation value is not necessarily data, and the technical effect of the application can be realized under the condition that the data are not acquired.
In the flight process of the aircraft, flight data of the aircraft can be obtained, wherein the inertial navigation data is position and attitude related information of the aircraft, and specific numerical values can be obtained through an acceleration sensor, a position and attitude sensor and the like. The aircraft position information can be related data obtained by a GPS system, or can be aircraft position information obtained by calculation according to an acceleration sensor, and the information represents the specific position of the aircraft in space. The channel information is information of an aircraft runway where the aircraft is located, specific information of each runway in each area is stored in an aircraft database, and after the channel is accurately positioned according to the position information, the channel position information can be obtained in the database.
The angle of the aircraft from the centerline may be calculated based on one or more data, for example, using a physical solution to the course signal to resolve the resolution signal.
Further, the generating the initial hardware redundancy signal according to the data acquired by the redundancy sensor includes:
acquiring a first wireless signal transmitted by a first redundancy sensor and a received first echo signal, and generating a first initial hardware redundancy signal according to the first wireless signal and the first echo signal;
and acquiring a second wireless signal transmitted by a second redundancy sensor and a second received echo signal, and generating a second initial hardware redundancy signal according to the second wireless signal and the second echo signal.
Illustratively, the onboard redundancy sensor is an onboard device that needs to derive an initial hardware redundancy signal from the signal returned by the signal emitting station. The two redundancy sensors transmit signals at the same time to respectively obtain corresponding initial hardware redundancy signals.
Further, the filtering the initial hardware redundancy signal based on the analytical redundancy signal to generate a hardware redundancy signal includes:
and respectively carrying out Kalman filtering on the first initial hardware redundancy signal and the second initial hardware redundancy signal based on the analysis redundancy signal so as to generate a first hardware redundancy signal and a second hardware redundancy signal.
Illustratively, data filtering is a data processing technology for removing noise and restoring real data, and Kalman filtering (Kalman filtering) is an algorithm for optimally estimating a system state by inputting and outputting observation data through a system by using a linear system state equation. The optimal estimate can also be seen as a filtering process, since the observed data includes the effects of noise and interference in the system.
In the scheme, the first initial hardware redundancy signal and the second initial hardware redundancy signal are processed through the Kalman filtering method, so that the first hardware redundancy signal and the second hardware redundancy signal which are relatively smooth are obtained, and the precision of voting results is improved.
Further, the judging the working state of the redundancy sensor according to the hardware redundancy signal includes:
calculating a first signal difference between the first hardware redundancy signal and the second hardware redundancy signal;
if the first signal difference value is smaller than a preset signal threshold value, determining that the redundancy sensor is in a normal state;
and if the first signal difference value is greater than or equal to the signal threshold value, acquiring a plurality of historical first signal difference values in a preset quantity or preset time in the historical data, and determining the working state of the redundancy sensor according to the first signal difference value and the historical first signal difference value.
For example, fig. 3 is a schematic diagram of signal monitoring voting according to an embodiment of the present application, as shown in fig. 3, after the analysis redundancy signal loc_analysis, the first hardware redundancy signal loc_1, and the second hardware redundancy signal loc_2 are obtained, consistency test is performed on the first hardware redundancy signal loc_1 and the second hardware redundancy signal loc_2.
If the data values obtained by the two redundancy sensors are relatively close, the first signal difference E1 between the two redundancy sensors is smaller than the signal threshold epsilon, which indicates that the two redundancy sensors detect relatively accurate course deviation signals. If the first signal difference E1 is larger, this indicates that the redundancy sensor has a possibility of failure. Further analysis is required based on the plurality of redundancy signals. The historical data is required to be acquired specifically, and accurate judgment is carried out according to the data in the voting process of the multi-frame signals.
Further, the determining the working state of the redundancy sensor according to the first signal difference value and the historical first signal difference value includes:
if the preset number of the historical first signal differences are all larger than or equal to the signal threshold value, determining that the redundancy sensor is in a continuous fault state, otherwise, determining that the redundancy sensor is in an instantaneous fault state; or alternatively, the first and second heat exchangers may be,
calculating a state parameter from a plurality of differences in the first signal difference and the historical first signal difference; wherein, when the difference value is greater than or equal to the signal threshold value, the value of the state parameter is increased by m; when the difference value is smaller than the signal threshold value, the value of the state parameter is reduced by n; and if the state parameter is greater than or equal to a preset parameter threshold, determining that the redundancy sensor is in a continuous fault state, otherwise, determining that the redundancy sensor is in an instantaneous fault state.
Illustratively, as shown in FIG. 3, this step provides two methods of determining faults, and consistency checking of the two sensor data.
The first is to determine whether the voting results of the multi-frame signals are all faults, for example, if the continuous 5-frame signals are abnormal, the redundancy sensor is determined to be in a continuous fault state, and if the continuous 5-frame signals are not continuously present, for example, if the 3-frame signals are present, the redundancy sensor is determined to be in an instantaneous fault state.
The second is to set a counter, the value of which is a state parameter, and the size of the state parameter represents the probability of the sensor to fail. The larger the value of the state parameter, the greater the probability that the sensor is faulty. For example, if the result of the 5-frame signal is obtained in the history data and 2 frames are normal signals, 3 frames are abnormal. When the signal is normal, the counter is increased by 5 each time, and when the signal is abnormal, the counter is decreased by 2 each time. The 2-frame signal counter is 10, the number of 3 anomalies is reduced by 6, the total count of the current counter is 4, if the threshold value is 5, the upper limit value is not exceeded, and the redundancy sensor is determined to be in an instantaneous fault state. If the upper Limit value is exceeded, i.e., count > Limit, indicating that the upper Limit is exceeded, the consistency check fails.
If the consistency detection is not passed, the fault of the LOC signal with double redundancy of hardware is indicated, and after the fault of the LOC signal is judged, the AP is disconnected, and the pilot drives the aircraft to finish landing.
Further, the monitoring voting on the hardware redundancy signal and the analysis redundancy signal to obtain a course deviation value includes:
and if the redundancy sensor is in a normal state, performing average value taking operation on the first hardware redundancy signal and the second hardware redundancy signal to obtain the heading channel deviation value.
For example, when the two redundancy sensors are operating normally, the average value of the two hardware redundancy signals is directly calculated, the average value is determined as a course deviation value, in addition, the analysis redundancy signal can be introduced, and the average value of the three signals is calculated as the course deviation value. In practical application, several redundancy signals are used, and an average value, a median value or other calculation methods can be selected to obtain the course deviation value, which is not limited in the application.
Further, the monitoring voting on the hardware redundancy signal and the analysis redundancy signal to obtain a course deviation value includes:
and if the redundancy sensor is in a continuous fault state, determining the course deviation value according to the analysis redundancy signal.
For example, if the two hardware redundancy signals always differ greatly, it indicates that at least one of the sensors is continuously malfunctioning, because the aircraft landing time is short, the hardware redundancy signals are temporarily stopped, and the analytical redundancy signals are directly selected to calculate the course deviation value.
Further, the monitoring voting on the hardware redundancy signal and the analysis redundancy signal to obtain a course deviation value includes:
if the redundancy sensor is in an instantaneous fault state, calculating a second signal difference value between the analysis redundancy signal and the first hardware redundancy signal;
calculating a second signal difference between the analytical redundancy signal and the first hardware redundancy signal;
calculating a third signal difference between the analytical redundancy signal and the second hardware redundancy signal;
calculating a mean value signal of the first hardware redundancy signal and the second hardware redundancy signal, and calculating a fourth signal difference value between the analysis redundancy signal and the mean value signal;
if the second signal difference value is smaller than the signal threshold value, determining that the second redundancy sensor is in an instantaneous fault state, and determining the heading channel deviation value according to the first hardware redundancy signal;
if the third signal difference value is smaller than the signal threshold value, determining that the first redundancy sensor is in an instantaneous fault state, and determining the heading channel deviation value according to the second hardware redundancy signal;
if the fourth signal difference value is smaller than the signal threshold value, determining that the first redundancy sensor and the second redundancy sensor are in an instantaneous fault state, and determining the heading channel deviation value according to the analysis redundancy signal;
and if the second signal difference value, the third signal difference value and the fourth signal difference value are all larger than or equal to the signal threshold value, acquiring the latest course deviation value from the historical data as the course deviation value.
Illustratively, as shown in FIG. 3, the resolution signal LOC_analysis is introduced in the monitoring vote when the counter aggregate does not exceed the upper limit or/and the continuous inconsistency does not exceed the threshold. And judging whether the errors of the analysis value and the dual-redundancy hardware signal value exceed a threshold or not, and judging whether the errors between the average value and the solution value of the hardware signal value exceed the threshold or not. Namely:
(1) The second signal difference E2 is compared with a signal threshold epsilon.
If e2= |loc_1-loc_analysis| < epsilon. The second redundancy sensor loc_2 is abnormal, the second redundancy sensor suffers an instantaneous failure, and the first hardware redundancy signal loc_1 is voted to be output.
(2) The third signal difference E3 is compared with a signal threshold epsilon.
If e3= |loc_2-loc_analysis| < epsilon. The first redundancy sensor loc_1 is abnormal, the first redundancy sensor suffers an instantaneous failure, and the second hardware redundancy signal LOC2 is voted to be output.
(3) The fourth signal difference E4 is compared with the signal threshold epsilon.
If e4= |loc_1+loc_2|/2- |loc_analysis| < epsilon. The resolution redundancy signal loc_analysis is at the first hardware redundancy signal loc_1.
And the second hardware redundancy signal LOC_2, the first redundancy sensor LOC_1 and the second redundancy sensor LOC_2 have instantaneous faults at the same time, and the voting output analyzes the redundancy signal LOC_analysis.
(4) If the above conditions are not satisfied, the first redundancy sensor loc_1 and the second redundancy sensor loc_2 have instantaneous faults at the same time and the analysis redundancy signal loc_analysis obtained by analysis is wrong, and the safety value, such as the last beat of the course deviation value voting value, is voted and output.
Through one or more of the above embodiments of the present application, at least the following technical effects can be achieved:
in the technical scheme disclosed by the application, the flight data is resolved to obtain the analytic redundancy signal, the initial hardware redundancy signal is obtained, the hardware redundancy signal is obtained through filtering of the analytic redundancy signal, and the hardware redundancy signal and the analytic redundancy signal are monitored and voted to obtain the course deviation value. The method and the device are based on the technical analysis of the virtual instrument landing equipment to obtain the analysis redundancy signal, and on the basis of not additionally increasing equipment, the physical analysis relation among the signals is utilized to analyze and obtain the course way signal of the automatic landing system, so that the number of instrument landing equipment is reduced, and wiring is facilitated. Redundancy monitoring voting is carried out by analyzing redundancy signals such as the redundancy signals and the hardware redundancy signals to serve as an important basis for detecting whether the hardware redundancy signals have faults or not, so that fault signals are accurately isolated, the voting signals are closer to a true value, and the integrity and usability of course deviation signals are improved. In addition, the smooth high-precision analytic redundancy signal is utilized to filter the initial hardware redundancy signal, noise signals are removed through signal fault detection and isolation, and the integrity and usability of the automatic landing system are improved.
In summary, the method introduces the analysis redundancy course deviation signal, on one hand, noise signals in the course deviation signal output by the instrument landing equipment are filtered by utilizing the analysis redundancy course deviation to improve the reliability of the analysis redundancy course deviation signal, and on the other hand, a three-redundancy monitoring voting framework is constructed according to different characteristics of the signals, so that isolation fault signals can be effectively detected, and the integrity and usability of the course deviation signal are improved.
Based on the same inventive concept as the method for monitoring and voting the course deviation signal in the embodiment of the present application, the embodiment of the present application provides a device for monitoring and voting the course deviation signal, please refer to fig. 4, the device includes:
the analysis module 201 is configured to generate an analysis redundancy signal according to flight data of the aircraft;
a data acquisition module 202, configured to generate an initial hardware redundancy signal according to the data acquired by the redundancy sensor;
a filtering module 203, configured to filter the initial hardware redundancy signal based on the resolution redundancy signal to generate a hardware redundancy signal;
and the voting module 204 is configured to determine the working state of the redundancy sensor according to the hardware redundancy signal, monitor and vote the hardware redundancy signal and the resolution redundancy signal to obtain a course deviation value if the redundancy sensor fails, and control the flight state of the aircraft according to the course deviation value.
Further, the parsing module 201 is further configured to:
acquiring the latest course deviation value from the historical data;
acquiring the flight data, wherein the flight data is one or more of aircraft inertial navigation data, aircraft position information and channel position information;
and performing object understanding calculation on the flight state of the aircraft based on the latest course deviation value and the flight data to generate the resolution residual signal.
Further, the data acquisition module 202 is further configured to:
acquiring a first wireless signal transmitted by a first redundancy sensor and a received first echo signal, and generating a first initial hardware redundancy signal according to the first wireless signal and the first echo signal;
and acquiring a second wireless signal transmitted by a second redundancy sensor and a second received echo signal, and generating a second initial hardware redundancy signal according to the second wireless signal and the second echo signal.
Further, the filtering module 203 is further configured to:
and respectively carrying out Kalman filtering on the first initial hardware redundancy signal and the second initial hardware redundancy signal based on the analysis redundancy signal so as to generate a first hardware redundancy signal and a second hardware redundancy signal.
Further, the device is further configured to:
calculating a first signal difference between the first hardware redundancy signal and the second hardware redundancy signal;
if the first signal difference value is smaller than a preset signal threshold value, determining that the redundancy sensor is in a normal state;
and if the first signal difference value is greater than or equal to the signal threshold value, acquiring a plurality of historical first signal difference values in a preset quantity or preset time in the historical data, and determining the working state of the redundancy sensor according to the first signal difference value and the historical first signal difference value.
Further, the device is further configured to:
if the preset number of the historical first signal differences are all larger than or equal to the signal threshold value, determining that the redundancy sensor is in a continuous fault state, otherwise, determining that the redundancy sensor is in an instantaneous fault state; or alternatively, the first and second heat exchangers may be,
calculating a state parameter from a plurality of differences in the first signal difference and the historical first signal difference; wherein, when the difference value is greater than or equal to the signal threshold value, the value of the state parameter is increased by m; when the difference value is smaller than the signal threshold value, the value of the state parameter is reduced by n; and if the state parameter is greater than or equal to a preset parameter threshold, determining that the redundancy sensor is in a continuous fault state, otherwise, determining that the redundancy sensor is in an instantaneous fault state.
Further, the voting module 204 is further configured to:
and if the redundancy sensor is in a normal state, performing average value taking operation on the first hardware redundancy signal and the second hardware redundancy signal to obtain the heading channel deviation value.
Further, the voting module 204 is further configured to:
and if the redundancy sensor is in a continuous fault state, determining the course deviation value according to the analysis redundancy signal.
Further, the voting module 204 is further configured to:
if the redundancy sensor is in an instantaneous fault state, calculating a second signal difference value between the analysis redundancy signal and the first hardware redundancy signal;
calculating a second signal difference between the analytical redundancy signal and the first hardware redundancy signal;
calculating a third signal difference between the analytical redundancy signal and the second hardware redundancy signal;
calculating a mean value signal of the first hardware redundancy signal and the second hardware redundancy signal, and calculating a fourth signal difference value between the analysis redundancy signal and the mean value signal;
if the second signal difference value is smaller than the signal threshold value, determining that the second redundancy sensor is in an instantaneous fault state, and determining the heading channel deviation value according to the first hardware redundancy signal;
if the third signal difference value is smaller than the signal threshold value, determining that the first redundancy sensor is in an instantaneous fault state, and determining the heading channel deviation value according to the second hardware redundancy signal;
if the fourth signal difference value is smaller than the signal threshold value, determining that the first redundancy sensor and the second redundancy sensor are in an instantaneous fault state, and determining the heading channel deviation value according to the analysis redundancy signal;
and if the second signal difference value, the third signal difference value and the fourth signal difference value are all larger than or equal to the signal threshold value, acquiring the latest course deviation value from the historical data as the course deviation value.
Other aspects and implementation details of the course deviation signal monitoring voting device are the same as or similar to those of the course deviation signal monitoring voting method, and are not described herein.
According to another aspect of the present application there is also provided a storage medium having stored therein a plurality of instructions adapted to be loaded by a processor to perform any of the course deviation signal monitoring voting methods described above.
In summary, although the present application has been described in terms of the preferred embodiments, the preferred embodiments are not limited to the above embodiments, and various modifications and changes can be made by one skilled in the art without departing from the spirit and scope of the application, and the scope of the application is defined by the appended claims.
Claims (11)
1. The course deviation signal monitoring voting method is characterized by comprising the following steps of:
generating an analytic redundancy signal according to flight data of the aircraft;
generating an initial hardware redundancy signal according to the data acquired by the redundancy sensor;
filtering the initial hardware redundancy signal based on the analytical redundancy signal to generate a hardware redundancy signal;
and judging the working state of the redundancy sensor according to the hardware redundancy signal, if the redundancy sensor fails, carrying out monitoring voting on the hardware redundancy signal and the analysis redundancy signal to obtain a course deviation value, and controlling the flight state of the aircraft according to the course deviation value.
2. The heading channel bias signal monitoring voting method of claim 1, wherein said generating a resolution residual signal from flight data of the aircraft comprises:
acquiring the latest course deviation value from the historical data;
acquiring the flight data, wherein the flight data is one or more of aircraft inertial navigation data, aircraft position information and channel position information;
and performing object understanding calculation on the flight state of the aircraft based on the latest course deviation value and the flight data to generate the resolution residual signal.
3. The heading channel bias signal monitoring voting method of claim 1, wherein generating an initial hardware redundancy signal from data acquired by a redundancy sensor comprises:
acquiring a first wireless signal transmitted by a first redundancy sensor and a received first echo signal, and generating a first initial hardware redundancy signal according to the first wireless signal and the first echo signal;
and acquiring a second wireless signal transmitted by a second redundancy sensor and a second received echo signal, and generating a second initial hardware redundancy signal according to the second wireless signal and the second echo signal.
4. The heading way bias signal monitoring voting method of claim 3, wherein said filtering the initial hardware redundancy signal based on the analytical redundancy signal to generate a hardware redundancy signal comprises:
and respectively carrying out Kalman filtering on the first initial hardware redundancy signal and the second initial hardware redundancy signal based on the analysis redundancy signal so as to generate a first hardware redundancy signal and a second hardware redundancy signal.
5. The method of course bias signal monitoring voting in accordance with claim 4, wherein said determining the operating state of the redundancy sensor in accordance with the hardware redundancy signal comprises:
calculating a first signal difference between the first hardware redundancy signal and the second hardware redundancy signal;
if the first signal difference value is smaller than a preset signal threshold value, determining that the redundancy sensor is in a normal state;
and if the first signal difference value is greater than or equal to the signal threshold value, acquiring a plurality of historical first signal difference values in a preset quantity or preset time in the historical data, and determining the working state of the redundancy sensor according to the first signal difference value and the historical first signal difference value.
6. The heading channel bias signal monitoring voting method of claim 5, wherein said determining an operating state of said redundancy sensor based on said first signal difference and said historical first signal difference comprises:
if the preset number of the historical first signal differences are all larger than or equal to the signal threshold value, determining that the redundancy sensor is in a continuous fault state, otherwise, determining that the redundancy sensor is in an instantaneous fault state; or alternatively, the first and second heat exchangers may be,
calculating a state parameter from a plurality of differences in the first signal difference and the historical first signal difference; wherein, when the difference value is greater than or equal to the signal threshold value, the value of the state parameter is increased by m; when the difference value is smaller than the signal threshold value, the value of the state parameter is reduced by n; and if the state parameter is greater than or equal to a preset parameter threshold, determining that the redundancy sensor is in a continuous fault state, otherwise, determining that the redundancy sensor is in an instantaneous fault state.
7. The method of course bias signal monitoring voting of claim 5, wherein said monitoring voting of said hardware redundancy signal and said analytical redundancy signal to obtain a course bias value comprises:
and if the redundancy sensor is in a normal state, performing average value taking operation on the first hardware redundancy signal and the second hardware redundancy signal to obtain the heading channel deviation value.
8. The method of course bias signal monitoring voting of claim 6, wherein said monitoring voting of said hardware redundancy signal and said analytical redundancy signal to obtain a course bias value comprises:
and if the redundancy sensor is in a continuous fault state, determining the course deviation value according to the analysis redundancy signal.
9. The method of course bias signal monitoring voting of claim 6, wherein said monitoring voting of said hardware redundancy signal and said analytical redundancy signal to obtain a course bias value comprises:
if the redundancy sensor is in an instantaneous fault state, calculating a second signal difference value between the analysis redundancy signal and the first hardware redundancy signal;
calculating a second signal difference between the analytical redundancy signal and the first hardware redundancy signal;
calculating a third signal difference between the analytical redundancy signal and the second hardware redundancy signal;
calculating a mean value signal of the first hardware redundancy signal and the second hardware redundancy signal, and calculating a fourth signal difference value between the analysis redundancy signal and the mean value signal;
if the second signal difference value is smaller than the signal threshold value, determining that the second redundancy sensor is in an instantaneous fault state, and determining the heading channel deviation value according to the first hardware redundancy signal;
if the third signal difference value is smaller than the signal threshold value, determining that the first redundancy sensor is in an instantaneous fault state, and determining the heading channel deviation value according to the second hardware redundancy signal;
if the fourth signal difference value is smaller than the signal threshold value, determining that the first redundancy sensor and the second redundancy sensor are in an instantaneous fault state, and determining the heading channel deviation value according to the analysis redundancy signal;
and if the second signal difference value, the third signal difference value and the fourth signal difference value are all larger than or equal to the signal threshold value, acquiring the latest course deviation value from the historical data as the course deviation value.
10. A course bias signal monitoring voting apparatus, the apparatus comprising:
the analysis module is used for generating an analysis redundancy signal according to the flight data of the aircraft;
the data acquisition module is used for generating an initial hardware redundancy signal according to the data acquired by the redundancy sensor;
the filtering module is used for filtering the initial hardware redundancy signal based on the analysis redundancy signal to generate a hardware redundancy signal;
and the voting module is used for judging the working state of the redundancy sensor according to the hardware redundancy signal, monitoring and voting the hardware redundancy signal and the analysis redundancy signal to obtain a course deviation value when the redundancy sensor fails, and controlling the flight state of the aircraft according to the course deviation value.
11. A storage medium having stored therein a plurality of instructions adapted to be loaded by a processor to perform the course deviation signal monitoring voting method of any one of claims 1 to 9.
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