CN115859481B - Simulation verification method and system for flight simulator - Google Patents
Simulation verification method and system for flight simulator Download PDFInfo
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- CN115859481B CN115859481B CN202310084220.6A CN202310084220A CN115859481B CN 115859481 B CN115859481 B CN 115859481B CN 202310084220 A CN202310084220 A CN 202310084220A CN 115859481 B CN115859481 B CN 115859481B
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Abstract
The invention relates to the field of simulation data verification, in particular to a simulation verification method and a system for a flight simulator, comprising the following steps: acquiring simulation audio data, real audio data and various audio sample data; obtaining a contrast audio data segment of the simulation audio data and each first reference data segment; obtaining a first error value and a first extended data segment according to each first reference data segment and the comparison audio data segment; obtaining a second extended data segment and a second error value according to the second reference data segment and the comparison audio data segment, and further obtaining a final extended data segment and a reliable decomposition algorithm; obtaining each decomposition result of the real audio data according to the reliable decomposition algorithm; and obtaining the reliability of each audio sample data according to each audio sample data and each decomposition result, and further correcting the audio sample data. The invention can obtain more stable audio decomposition effect and more accurate simulation verification result.
Description
Technical Field
The invention relates to the field of simulation data verification, in particular to a simulation verification method and system for a flight simulator.
Background
In the simulation experiment of the flight simulator, the audio simulation is an important component part in the flight simulator, and can bring better immersive feeling to the flight simulation process. The simulation system can realize the audio simulation in the simulation system of the flight simulator through the existing audio simulation software, but in the audio simulation process, if the simulation parameters of a certain section of simulation used audio are improperly set, the final audio simulation result is not true enough, and the immersion of the flight simulator is destroyed.
In order to ensure that the simulation process of the flight simulator is sufficiently realistic, the audio simulation data of the flight simulator needs to be verified. The simulation audio data is subjected to audio decomposition, and the simulation decomposition result is compared with the real audio decomposition result, so that verification of the simulation audio data is completed, and the simulation parameter setting unsuitable part of the audio used in the simulation process of the flight simulator can be found.
However, after the simulated audio data is subjected to audio decomposition, when a part with improper parameter setting of the simulated data is searched, if the effect of the simulated audio data on audio decomposition is poor, the final simulated verification effect is affected; when audio data is decomposed through an empirical mode decomposition algorithm, that is, an EMD algorithm, although the EMD algorithm can solve the mode superposition problem through combination with an ICA algorithm, an end effect still exists, and although the end effect can be restrained through an extremum continuation method, if the extremum point expansion effect is poor, a follow-up audio decomposition result is inaccurate, and the final simulation verification effect is affected.
Disclosure of Invention
The invention provides a simulation verification method and a simulation verification system for a flight simulator, which aim to solve the existing problems.
The invention discloses a simulation verification method and a simulation verification system for a flight simulator, which adopt the following technical scheme:
one embodiment of the present invention provides a method of simulation verification of a flight simulator, the method comprising the steps of:
acquiring simulation audio data, real audio data and various audio sample data used in a simulation process of a flight simulator;
setting a sliding window, and obtaining a comparison audio data segment of the simulation audio data and each first reference data segment according to the sliding window; obtaining the difference degree of each first reference data segment according to the audio data at the corresponding position of each first reference data segment and the corresponding position of the comparison audio data segment; taking the minimum difference degree of all the obtained difference degrees as a first error value, and obtaining a first extended data segment according to a first reference data segment corresponding to the minimum difference degree;
acquiring a second reference data segment, and acquiring a second extended data segment and a second error value according to the second reference data segment and the comparison audio data segment; according to the first error value and the second error value, carrying out data fusion on the first extension data segment and the second extension data segment to obtain a final extension data segment;
obtaining a reliable decomposition algorithm according to the final extended data segment; obtaining each decomposition result of the real audio data according to the reliable decomposition algorithm; obtaining the reliability of each audio sample data according to the approximation degree between each audio sample data and each decomposition result;
and performing simulation verification on the audio sample data according to the reliability of each audio sample data.
Preferably, the method for obtaining the contrast audio data segment of the simulated audio data and each first reference data according to the sliding window includes:
after the tail end of the sliding window is aligned with the tail end of the simulation audio data, the audio data in the sliding window are used as comparison audio data segments of the simulation audio data; sliding the sliding window from the initial end of the simulation audio data to the tail end of the simulation audio data, and taking the audio data in the sliding window corresponding to each sliding preset length as a first reference data segment to obtain each first reference data segment.
Preferably, the step of obtaining the degree of difference between the first reference data segments includes:
calculating absolute values of differences between the audio data in the first reference data segments and the audio data in the corresponding positions of the comparison audio data segments, and taking the obtained absolute values as error values corresponding to the audio data; and calculating the product of the error value corresponding to each audio data in each first reference data segment and the serial number of each audio data, accumulating the products corresponding to all the audio data in each first reference data segment, and taking the accumulated result as the difference degree of each first reference data segment.
Preferably, the method for obtaining the first extended data segment according to the first reference data segment corresponding to the minimum difference degree includes:
and starting from the tail end of the first reference data segment corresponding to the minimum difference degree, acquiring an audio data segment with the length equal to the length of the sliding window, and taking the acquired audio data segment as a first extension data segment.
Preferably, the method for obtaining the second extended data segment and the second error value according to the second reference data segment and the comparative audio data segment includes:
obtaining predicted values corresponding to all sampling points in a second reference data segment according to coordinate values of all sampling points in the second reference data segment and polynomial expressions of comparison audio frequency segments, wherein each sampling point in the second reference data segment corresponds to one audio frequency data value, calculating absolute values of differences between the audio frequency data values corresponding to all sampling points in the second reference data segment and the predicted values, taking the obtained absolute values as error values corresponding to all sampling points, accumulating the error values of all sampling points in the second reference data segment, and taking the accumulated result as a second error value;
and starting the tail end of the contrast audio data segment, acquiring the audio data segment with the length equal to the length of the sliding window, taking the acquired audio data segment as a second extension data segment, and acquiring the audio data of each sampling point in the second extension data segment according to the coordinate value of each sampling point in the second extension data segment and the polynomial expression of the contrast audio data segment.
Preferably, the obtaining expression of the final extended data segment is:
in the method, in the process of the invention,
the audio data value corresponding to the j-th sampling point in the final extension data segment is obtained; />
Is the second error value; c is the first error value, ">
For the audio data value corresponding to the j-th sampling point in the first extended data segment, +.>
And the audio data value corresponding to the j-th sampling point in the second continuation data segment is obtained.
Preferably, the reliable decomposition algorithm refers to: the input data is an empirical mode decomposition algorithm of the final extended data segment.
Preferably, the method for obtaining the reliability of each audio sample data comprises the following steps: the maximum approximation degree of all approximation degrees corresponding to the respective audio sample data is taken as the reliability of the respective audio sample data.
Another embodiment of the present invention provides a simulation verification system for a flight simulator, the system including an audio data acquisition module, a final extended data segment acquisition module, an audio sample data reliability calculation module, and an audio sample data correction module, wherein:
the audio data acquisition module is used for acquiring simulation audio data, real audio data of the flight simulator and various audio sample data used in the simulation process;
the final extension data segment acquisition module is used for setting a sliding window and obtaining a comparison audio data segment of the simulation audio data and each first reference data segment according to the sliding window; obtaining the difference degree of each first reference data segment according to the audio data at the corresponding position of each first reference data segment and the corresponding position of the comparison audio data segment; taking the minimum difference degree of all the obtained difference degrees as a first error value, and obtaining a first extended data segment according to a first reference data segment corresponding to the minimum difference degree;
acquiring a second reference data segment, and acquiring a second extended data segment and a second error value according to the second reference data segment and the comparison audio data segment; according to the first error value and the second error value, carrying out data fusion on the first extension data segment and the second extension data segment to obtain a final extension data segment;
the audio sample data reliability calculation module is used for obtaining a reliability decomposition algorithm according to the final extension data segment; obtaining each decomposition result of the real audio data according to the reliable decomposition algorithm; obtaining the reliability of each audio sample data according to the approximation degree between each audio sample data and each decomposition result;
and the audio sample data correction module is used for carrying out simulation verification on the audio sample data according to the reliability of each audio sample data.
The beneficial effects of the invention are as follows: firstly, weighting and fusing the extension data segments obtained by using different polarity value extension methods, so that the method has a more stable audio decomposition effect when decomposing real audio, can ensure that an endpoint effect-inhibiting reliable decomposition algorithm is adopted, the error of the obtained audio decomposition data is smaller, then, comparing each decomposition result of the real audio data with each audio sample data to obtain the reliability of each audio sample data, and finally, detecting the reliability of each audio sample data, thereby correcting the audio sample data with abnormal reliability and completing the simulation verification of a flight simulator.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of steps of a method of simulation verification of a flight simulator of the present invention;
FIG. 2 is a block diagram of a simulation verification system for a flight simulator of the present invention;
FIG. 3 is a schematic diagram of a comparative audio data segment of a method of simulated verification of a flight simulator according to the present invention.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following description refers to the specific implementation, structure, characteristics and effects of a simulation verification method and system for a flight simulator according to the invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The following specifically describes a specific scheme of a simulation verification method for a flight simulator provided by the invention with reference to the accompanying drawings.
Referring to fig. 1, a flowchart of steps of a method for simulating and verifying a flight simulator according to an embodiment of the invention is shown, the method includes the following steps:
step S001: and acquiring simulation audio data, real audio data and various audio sample data used in a simulation process of the flight simulator.
And acquiring the flight equipment corresponding to the flight simulator, and corresponding to the real audio data in the real scene in the simulation process. The method comprises the steps of installing microphone equipment in the flying equipment, and acquiring real audio data of the flying equipment in a real scene through the microphone equipment. The flight simulator has a plurality of audio simulation software, an implementer can adjust according to specific implementation scenes, and the embodiment uses FLIGHTLAB software to carry out audio simulation as an embodiment. The audio simulation process of the flight simulator is a process well known to those skilled in the art, and will not be described herein. Acquiring each piece of audio sample data for simulation, and simulating each piece of audio sample data by using simulation software to obtain simulated audio data;
the value of each audio data in the obtained simulated audio data and the real audio data is the audio amplitude obtained by each acquisition, and each acquisition is called a sampling point, so that each sampling point in the simulated audio data and the real audio data corresponds to one audio data.
Step S002: and carrying out data fusion on the first extension data segment and the second extension data segment according to the first error value and the second error value to obtain a final extension data segment.
Because the audio data of the flight simulator are one-dimensional data, the ICA algorithm cannot be directly adopted for blind source separation, and the ICA algorithm needs multi-channel data input; the EMD algorithm can obtain a good audio characteristic decomposition effect when processing non-stationary and non-linear signals, and can realize self-adaptive audio decomposition. However, in the audio decomposition result of the EMD algorithm, a modal aliasing phenomenon may occur, so that a plurality of IMF components decomposed by the EMD algorithm may be used as input of the ICA algorithm, and the modal aliasing phenomenon in the EMD algorithm is solved by the ICA algorithm, so as to obtain a final audio data decomposition result, so that the EMD-ICA algorithm is widely applied.
However, the audio decomposition result obtained by using the EMD algorithm often has an end-point effect problem, and the end-point effect is usually solved by using an extremum extension method, which is to perform extremum point extension on data to eliminate the end-point effect. When the extreme point extension is carried out, a plurality of extreme point extension methods exist, but the purpose is to enable the extended data to be more attached to each audio sample data, so that after the simulation audio data extended by the extreme point are decomposed, the difference between the obtained simulation audio data decomposition result and the simulation audio data is smaller. If the extremum reduction method is used, the simulated audio data is shortened, the decomposition result of the obtained simulated audio data is shortened, and a larger error is generated when the approximation degree is calculated according to the decomposition result of the obtained simulated audio data and the simulated audio data.
In order to enable the extended data to be more attached to the simulated audio data, the existing extremum extension method generally selects the audio data segment closest to the two ends of the simulated audio data from the simulated audio data to carry out waveform data matching and then carries out extremum point extension, but if the simulated audio data does not have the audio data segment similar to the two ends of the simulated audio data, the extension method such as data fitting prediction or mirror image/translation is needed to carry out extension. In the embodiment, two extremum extension methods are predicted by adopting waveform matching and data fitting, data fusion is carried out on extension data segments of the two extremum extension methods, and a fusion result is used as a final extension data segment.
Taking extension of the right end of the simulated audio data as an example, the specific process of obtaining the final extended data segment is as follows:
1. the extremum extension is carried out on the simulated audio data by utilizing a waveform matching method, and the specific process is as follows:
setting a sliding window with the length A, starting from the rightmost data of the simulated audio data, intercepting the audio data with the length A in the left direction to obtain a comparison audio data segment
The schematic diagram of the acquisition of the comparative audio data segment is shown in fig. 3, wherein the rightmost end of the sliding window 102 is aligned with the rightmost end of the dummy audio data 103, and the audio data in the sliding window forms the comparative audio data segment->
The corresponding sliding window center point is 101, and in this embodiment, it is necessary to ensure the contrast audio data segment
The corresponding sliding window from the center point to the rightmost end of the simulated audio data at least comprises 2 extreme points, in this embodiment, a=20, and the implementer can adjust according to the final implementation scene.
Then starting from the leftmost end of the whole simulation audio data, intercepting the simulation audio data by using a sliding window, namely aligning the leftmost end of the sliding window with the leftmost end of the simulation audio data, acquiring the audio data in the sliding window at the moment, obtaining a first reference data segment, and setting a preset length as
Then acquiring the audio frequency in the sliding window corresponding to each sliding preset length of the sliding windowObtaining a new first reference data segment until the new first reference data segment slides to the rightmost end of the simulated audio data, and obtaining a plurality of first reference data segments; calculating the respective first reference data segment and the contrast audio data segment +.>
And taking the absolute value of the obtained difference value as the error value of the corresponding sampling point of each first reference data segment.
It should be noted that, in this embodiment, the leftmost end of the sliding window (or the simulated audio data) is also referred to as the start end of the sliding window (or the simulated audio data), and the rightmost end of the sliding window (or the simulated audio data) is also referred to as the end of the sliding window (or the simulated audio data).
Comparing audio data segments as extreme values for emulating audio data extending to the right
The more important the data closer to the right in the middle is, thus acquiring a contrast audio data segment +.>
The Euclidean distance from each sampling point to the rightmost sampling point in the pair, the smaller the Euclidean distance is, the more important the corresponding audio data is when extremum extension is carried out, thereby obtaining each first reference data segment and each first reference data segment
Wherein the i-th first reference data segment is recorded with +.>
The degree of difference between is->
Then:
wherein, the liquid crystal display device comprises a liquid crystal display device,
the jth audio data and +.>
The absolute value of the difference between the j-th audio data, i.e. the error value corresponding to the j-th sampling point of the i-th first reference data segment; since the lengths of the first reference data segments are all fixed, the Euclidean distance of each audio data can be obtained according to the sequence number of each audio data, the smaller the sequence number, the larger the distance between the sequence number and the rightmost sampling point of the comparison audio data segment is, the less important the corresponding audio data is, otherwise, the larger the sequence number is, the more important the corresponding audio data is, so the embodiment uses->
Indicating the importance level of the jth audio data.
Taking the minimum difference degree in all the first reference data segments as the error value of waveform matching, marking the error value as a first error value C, selecting the first reference data segment corresponding to the minimum difference degree, and marking the first reference data segment as
First reference data section +.>
And->
Is most similar, then from +.>
Taking the audio data segment with the length A to the right, taking the obtained audio data segment as a waveform matching extension data segment, and recording the waveform matching extension data segment as a first extension data segment, wherein the extension data segment obtained according to the most similar first reference data segment can minimize the error between the simulation audio data obtained after extension and the original simulation audio data.
2. And carrying out extremum extension on the simulated audio data by utilizing data fitting prediction, wherein the specific process is as follows:
since the right end of the simulated audio data is extended, i.e. to
The data on the right side are fit predicted, whereas +.>
Is the rightmost end of the emulated audio data, thus +.>
To the right of (a) there is no audio data, so it is necessary to follow +.>
The audio data on the left side is predicted so that the audio data segment is compared>
To the left, i.e. the rightmost side of the sliding window is left-hand with +.>
After the leftmost alignment of (a), the audio data segment formed by each audio data in the sliding window is marked as a second reference data segment +.>
；
Comparing audio data segments using a polynomial fitting algorithm
Polynomial fitting is performed on each audio data of (a) to obtain a comparison audio data segment +.>
Polynomial expression of (2) will +.>
The coordinate value of each sampling point is substituted into +.>
The result is taken as ++>
The second reference data segment +.>
The predicted values corresponding to all sampling points in the data set form an audio predicted data segment, and the audio predicted data segment and a second reference data segment are calculated>
The absolute value of the obtained difference value is used as the error value corresponding to the corresponding sampling point in the audio prediction data segment, the accumulated sum of the error values corresponding to all the sampling points in the audio prediction data segment is calculated, the obtained accumulated sum is used as the error value of the data fitting prediction, and the error value is recorded as a second error value +.>
。
Wherein in the audio prediction data segment predicted using data fitting prediction, the audio data of each sampling point is compared with the second reference data segment
The greater the difference between the audio data of the corresponding sampling points,the lower the accuracy of the fit prediction, i.e. +.>
The larger the fitting prediction accuracy is, the lower the fitting prediction accuracy is, otherwise, the higher the fitting prediction accuracy is;
the method for acquiring the extended data segment according to the data fitting prediction method comprises the following steps: from contrasting segments of audio data
To right, i.e. the leftmost side of the sliding window is left +.>
After the rightmost side of the audio data segment is aligned, the audio data segment formed by each audio data in the sliding window is not existed in the obtained audio data segment, and the audio data of each sampling point in the audio data segment needs to be predicted, for example, for the j-th sampling point of the audio data segment, the coordinate value of the j-th sampling point is substituted into the comparison audio data segment>
The obtained result is taken as the predicted audio data corresponding to the j-th sampling point, and the like, so as to obtain the predicted audio data of each sampling point in the audio data segment, and the audio data segment at the moment is called a continuation data segment corresponding to the data fitting prediction, namely a second continuation data segment;
according to the first error value and the second error value, carrying out data fusion on the first extension data segment and the second extension data segment to obtain a final extension data segment, wherein the audio data value corresponding to the j-th sampling point of the final extension data segment is as follows:
in the method, in the process of the invention,
for the j-th sample in the final extended data segmentAudio data values corresponding to the points; />
Is the second error value; c is the first error value, ">
For the audio data value corresponding to the j-th sampling point in the first extended data segment, +.>
And the audio data value corresponding to the j-th sampling point in the second continuation data segment is obtained. />
When the first error value and the second error value are larger, the error of the obtained simulated audio data is larger after the extremum extension is carried out on the simulated audio data respectively in the first extended data segment obtained according to waveform matching and the second extended data segment obtained by data fitting prediction; when the first error value and the second error value are smaller, the error of the obtained final extension data segment is smaller when the first extension data segment and the second extension data segment are subjected to data fusion according to the first error value and the second error value, so that the final extension data segment can obtain smaller error, for the two extremum extension methods, a higher reference weight is set for the party with smaller error value, the embodiment firstly obtains the sum of the first error value and the second error value, then calculates the ratio between the first error value, the second error value and the obtained sum, respectively calculates the difference between 1.0 and each ratio, takes each obtained difference as the reference weight of each extension data segment, and thus, the sum of the reference weights corresponding to the extension data segments obtained by the two extremum extension methods is 1, for example, for the extension data segment with waveform matching, the reference weights of the extension data segments are 1
That is, the reference weight of the first continuation data section is +.>
Similarly, the data fitting prediction is obtained to correspond to the extended data segment, namelyThe reference weight of the two continuation data segments is +.>
Thus, the final extension data segment can be more biased to the extension segment corresponding to the extension method with smaller error.
Repeating the method to obtain the audio data value corresponding to each sampling point in the final extension data segment to obtain the final extension data segment.
Because the flight environment of the flight simulator is complex, the embodiment can have more robustness to the adaptive scene by selecting two extremum extension methods, and the final extension data segment obtained finally has smaller error value by weighting and fusing the extension data segments corresponding to the two extremum extension methods, and the final extension data segment is used as the input data of the EMD algorithm, so that the end point effect of the EMD algorithm is inhibited, and the reliable EMD decomposition algorithm, namely the decomposition algorithm is obtained.
Step S003: obtaining a reliable decomposition algorithm according to the final extended data segment; obtaining each decomposition result of the real audio data according to the reliable decomposition algorithm; and obtaining the reliability of each audio sample data according to the approximation degree between each audio sample data and each decomposition result.
After the reliable decomposition algorithm is obtained, the reliable decomposition algorithm is combined with the ICA algorithm to obtain a reliable audio decomposition algorithm, the collected real audio data is decomposed through the reliable audio decomposition algorithm, namely, the real audio data is decomposed by the reliable decomposition algorithm, and a plurality of IMF components obtained are used as input of the ICA algorithm to obtain each decomposition result of the real audio data. Since the order and amplitude values of the signal sources to which the decomposition results of the ICA algorithm belong are uncertain, the approximation degree between each audio sample data and all the decomposition results is calculated by the DTW algorithm, and the maximum approximation degree of each audio sample data is taken as the reliability of each audio sample data.
Step S004: and correcting the audio sample data according to the reliability of each audio sample data to complete the simulation verification of the flight simulator.
After the reliability of each audio sample data is obtained, the reliability of each audio sample data is detected by using an anomaly detection algorithm, such as a box diagram, so that the reliability of each anomaly is obtained, and the audio sample data corresponding to the reliability of each anomaly is corrected, wherein the correction process is carried out by an audio sample data with related audio simulation working experience personnel for correcting the audio sample data with simulation errors, namely, the simulation verification of the audio sample data of the flight simulator is completed by correcting the audio sample data with the reliability anomaly.
Through the steps, simulation verification of the flight simulator is completed.
Another embodiment of the present invention provides a simulation verification system for a flight simulator, as shown in fig. 2, comprising the following modules:
the audio data acquisition module is used for acquiring simulation audio data, real audio data of the flight simulator and various audio sample data used in the simulation process;
the final extension data segment acquisition module is used for setting a sliding window and obtaining a comparison audio data segment of the simulation audio data and each first reference data segment according to the sliding window; obtaining the difference degree of each first reference data segment according to the audio data at the corresponding position of each first reference data segment and the corresponding position of the comparison audio data segment; taking the minimum difference degree of all the obtained difference degrees as a first error value, and obtaining a first extended data segment according to a first reference data segment corresponding to the minimum difference degree;
acquiring a second reference data segment, and acquiring a second extended data segment and a second error value according to the second reference data segment and the comparison audio data segment; according to the first error value and the second error value, carrying out data fusion on the first extension data segment and the second extension data segment to obtain a final extension data segment;
the audio sample data reliability calculation module is used for obtaining a reliability decomposition algorithm according to the final extension data segment; obtaining each decomposition result of the real audio data according to the reliable decomposition algorithm; obtaining the reliability of each audio sample data according to the approximation degree between each audio sample data and each decomposition result;
and the audio sample data correction module is used for carrying out simulation verification on the audio sample data according to the reliability of each audio sample data.
According to the embodiment, firstly, weighting fusion is carried out on the extension data segments obtained by using different polarity value extension methods, so that a more stable audio decomposition effect is achieved when real audio is decomposed, a reliable decomposition algorithm for inhibiting an end effect can be achieved, the error of the obtained audio decomposition data is smaller, then, each decomposition result of the real audio data is compared with each audio sample data to obtain the reliability of each audio sample data, finally, the reliability of each audio sample data is detected, and therefore the audio sample data with abnormal reliability is corrected, and simulation verification of a flight simulator is completed.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (9)
1. A method of simulation verification of a flight simulator, the method comprising the steps of:
acquiring simulation audio data, real audio data and various audio sample data used in a simulation process of a flight simulator;
setting a sliding window, and obtaining a comparison audio data segment of the simulation audio data and each first reference data segment according to the sliding window; obtaining the difference degree of each first reference data segment according to the audio data at the corresponding position of each first reference data segment and the corresponding position of the comparison audio data segment; taking the minimum difference degree of all the obtained difference degrees as a first error value, and obtaining a first extended data segment according to a first reference data segment corresponding to the minimum difference degree;
acquiring a second reference data segment, and acquiring a second extended data segment and a second error value according to the second reference data segment and the comparison audio data segment; according to the first error value and the second error value, carrying out data fusion on the first extension data segment and the second extension data segment to obtain a final extension data segment;
obtaining a reliable decomposition algorithm according to the final extended data segment; obtaining each decomposition result of the real audio data according to the reliable decomposition algorithm; obtaining the reliability of each audio sample data according to the approximation degree between each audio sample data and each decomposition result;
and performing simulation verification on the audio sample data according to the reliability of each audio sample data.
2. A method of simulation verification of a flight simulator according to claim 1, wherein the method of deriving the contrasting audio data segments of simulated audio data and the respective first reference data from a sliding window comprises:
after the tail end of the sliding window is aligned with the tail end of the simulation audio data, the audio data in the sliding window are used as comparison audio data segments of the simulation audio data; sliding the sliding window from the initial end of the simulation audio data to the tail end of the simulation audio data, and taking the audio data in the sliding window corresponding to each sliding preset length as a first reference data segment to obtain each first reference data segment.
3. A method of simulation verification of a flight simulator according to claim 1, wherein the step of obtaining the degree of difference of the respective first reference data segments comprises:
calculating absolute values of differences between the audio data in the first reference data segments and the audio data in the corresponding positions of the comparison audio data segments, and taking the obtained absolute values as error values corresponding to the audio data; and calculating the product of the error value corresponding to each audio data in each first reference data segment and the serial number of each audio data, accumulating the products corresponding to all the audio data in each first reference data segment, and taking the accumulated result as the difference degree of each first reference data segment.
4. The method for simulating and verifying a flight simulator according to claim 1, wherein the method for obtaining the first extended data segment according to the first reference data segment corresponding to the minimum difference degree is as follows:
and starting from the tail end of the first reference data segment corresponding to the minimum difference degree, acquiring an audio data segment with the length equal to the length of the sliding window, and taking the acquired audio data segment as a first extension data segment.
5. The method for simulating and verifying a flight simulator according to claim 1, wherein the method for obtaining the second extended data segment and the second error value according to the second reference data segment and the comparative audio data segment comprises:
obtaining predicted values corresponding to all sampling points in a second reference data segment according to coordinate values of all sampling points in the second reference data segment and polynomial expressions of comparison audio frequency segments, wherein each sampling point in the second reference data segment corresponds to one audio frequency data value, calculating absolute values of differences between the audio frequency data values corresponding to all sampling points in the second reference data segment and the predicted values, taking the obtained absolute values as error values corresponding to all sampling points, accumulating the error values of all sampling points in the second reference data segment, and taking the accumulated result as a second error value;
and starting the tail end of the contrast audio data segment, acquiring the audio data segment with the length equal to the length of the sliding window, taking the acquired audio data segment as a second extension data segment, and acquiring the audio data of each sampling point in the second extension data segment according to the coordinate value of each sampling point in the second extension data segment and the polynomial expression of the contrast audio data segment.
6. The method for simulation verification of a flight simulator according to claim 1, wherein the obtaining expression of the final extended data segment is:
in the method, in the process of the invention,
the audio data value corresponding to the j-th sampling point in the final extension data segment is obtained; />
Is the second error value; c is the first error value, ">
For the audio data value corresponding to the j-th sampling point in the first extended data segment, +.>
And the audio data value corresponding to the j-th sampling point in the second continuation data segment is obtained.
7. A method of simulation verification of a flight simulator according to claim 1, wherein the reliability decomposition algorithm is: the input data is an empirical mode decomposition algorithm of the final extended data segment.
8. The method for simulating and verifying a flight simulator according to claim 1, wherein the method for acquiring the reliability of each audio sample data comprises the steps of: the maximum approximation degree of all approximation degrees corresponding to the respective audio sample data is taken as the reliability of the respective audio sample data.
9. A simulation verification system for a flight simulator, the system comprising the following modules:
the audio data acquisition module is used for acquiring simulation audio data, real audio data of the flight simulator and various audio sample data used in the simulation process;
the final extension data segment acquisition module is used for setting a sliding window and obtaining a comparison audio data segment of the simulation audio data and each first reference data segment according to the sliding window; obtaining the difference degree of each first reference data segment according to the audio data at the corresponding position of each first reference data segment and the corresponding position of the comparison audio data segment; taking the minimum difference degree of all the obtained difference degrees as a first error value, and obtaining a first extended data segment according to a first reference data segment corresponding to the minimum difference degree;
acquiring a second reference data segment, and acquiring a second extended data segment and a second error value according to the second reference data segment and the comparison audio data segment; according to the first error value and the second error value, carrying out data fusion on the first extension data segment and the second extension data segment to obtain a final extension data segment;
the audio sample data reliability calculation module is used for obtaining a reliability decomposition algorithm according to the final extension data segment; obtaining each decomposition result of the real audio data according to the reliable decomposition algorithm; obtaining the reliability of each audio sample data according to the approximation degree between each audio sample data and each decomposition result;
and the audio sample data correction module is used for carrying out simulation verification on the audio sample data according to the reliability of each audio sample data.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101960866A (en) * | 2007-03-01 | 2011-01-26 | 杰里·马哈布比 | Audio spatialization and environment simulation |
| CN110708651A (en) * | 2019-09-25 | 2020-01-17 | 天津大学 | Hearing aid squeal detection and suppression method and device based on segmented trapped wave |
| CN112380621A (en) * | 2020-11-12 | 2021-02-19 | 北京航空航天大学 | Flight simulator sound simulation method based on ASIO |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150276845A1 (en) * | 2014-03-25 | 2015-10-01 | University Of Idaho | Causality enforcement for electrical interconnects through periodic continuations |
| GB2530765A (en) * | 2014-10-01 | 2016-04-06 | Bae Systems Plc | Simulation system |
-
2023
- 2023-02-09 CN CN202310084220.6A patent/CN115859481B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101960866A (en) * | 2007-03-01 | 2011-01-26 | 杰里·马哈布比 | Audio spatialization and environment simulation |
| CN110708651A (en) * | 2019-09-25 | 2020-01-17 | 天津大学 | Hearing aid squeal detection and suppression method and device based on segmented trapped wave |
| CN112380621A (en) * | 2020-11-12 | 2021-02-19 | 北京航空航天大学 | Flight simulator sound simulation method based on ASIO |
Non-Patent Citations (5)
| Title |
|---|
| A.Broatch等.Dynamic mode decomposition of the acoustic field in radial compressors.Aerospace Science and Technology.2019,第90卷全文. * |
| Poly Rani Ghosh等.Spectral Analysis of Audio Signals with Noise Assisted Empirical Mode Decomposition.International journal of signal processing.2015,第8卷(第4期),全文. * |
| 季策 ; 孙梦雪 ; 张君 ; .基于EMD改进算法的欠定混合盲分离.东北大学学报(自然科学版).2018,(08),全文. * |
| 徐世艳 ; .基于延拓技术的经验模态分解改进算法.吉林大学学报(信息科学版).2009,(04),全文. * |
| 王尔馥 ; 张乃通 ; 孟维晓 ; .AWGN信道中盲源分离的时频联合两步消噪预处理方案.哈尔滨工程大学学报.2009,(04),全文. * |
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