Methods, systems, and media for digital synthesis of engine noise for aircraft flight training simulators

Abstract

This invention relates to the field of flight simulator technology, and discloses a method, system, and medium for digital synthesis of engine noise in an aircraft flight training simulator. The method first collects audio samples of a real aircraft engine under multiple different operating conditions and simultaneously records the corresponding engine operating parameters. After performing spectral analysis on the audio samples, a spectral difference database of engine noise is constructed. Then, in the real-time audio rendering thread of the simulator's host, the current engine operating parameters are received and interpolated and dynamically filtered in conjunction with the spectral difference database to output the synthesized engine noise audio signal. This invention uses spectral difference analysis and dynamic filtering control to achieve engine noise synthesis, and directly extracts spectral features from real aircraft recordings to drive the synthesis process. While ensuring high fidelity in acoustic characteristics, it achieves a flight simulator engine noise synthesis output that combines high fidelity, high real-time performance, and smooth continuity.

Description

Technical Field

[0001] This invention relates to the field of flight simulator technology, particularly sound simulation, and more specifically to a method, system, and medium for digital synthesis of engine noise in an aircraft flight training simulator. Background Technology

[0002] Currently, aircraft flight training simulators are increasingly demanding high-fidelity and immersive training experiences. Acoustic simulation, especially engine noise simulation, is a key element in creating this immersive experience. Existing simulator engine sound synthesis mainly includes audio sampling and playback, physical modeling synthesis, and wavetable synthesis and modulation techniques. Audio sampling and playback is the most traditional and widely used method. It records engine sounds under various operating conditions (such as different throttle positions, flight altitudes, airspeeds, and attitudes) on a real aircraft (e.g., in the cockpit, outside the cabin, at different distances and angles). It typically uses techniques such as crossfade-in / fade-out and multi-level looping to achieve smooth transitions between different states, forming a vast audio sample library. Physical modeling synthesis simulates the physical process of engine noise generation through mathematical equations and algorithms. It is usually based on aeroacoustic principles, modeling the main noise sources inside the engine (such as compressor / fan noise, turbine noise, combustion noise, and jet noise), establishing the functional relationship between these noise sources and core engine parameters (such as engine speed, airflow velocity, temperature, and pressure), and calculating and generating corresponding sound signals in real time. Wavetable synthesis and modulation uses a set of basic waveforms (wavetables) as sound material, and then dynamically changes the properties of these waveforms (such as pitch, harmonic structure, amplitude) through low-frequency oscillators (LFOs), envelope modulation, filter modulation, etc., thereby simulating the effect of engine sound changing with operating conditions.

[0003] Some advanced simulators employ hybrid technology, combining the advantages of the above methods. They use sample playback to ensure the authenticity of the basic sound, while supplementing it with physical modeling or parametric modulation to adjust certain characteristics of the sound in real time (such as the Doppler effect of jet noise and low-frequency resonance caused by cockpit structural vibration) to cope with continuous parameter changes that the sampling library cannot cover.

[0004] While the aforementioned technologies are widely used in flight simulators, their inherent limitations make it difficult to meet the stringent requirements of high-level flight simulators (such as Class D) for sound simulation realism, real-time performance, and flexibility. For example, audio sampling playback relies on discrete sample points. Even with a large number of samples and balancing algorithms, perceptible stair-step effects and repetitiveness are still difficult to avoid when parameters change continuously (such as slow throttle input), disrupting immersion and lacking realistic continuity. Moreover, the sample library is large, lacks flexibility, and is difficult to adapt to new aircraft models. Physical modeling synthesis technology relies on high-precision aeroacoustic models, involving complex differential partial equations and fluid calculations, requiring enormous computational resources and making it difficult to implement in simulator systems that guarantee high real-time performance (low latency). Although simplified models can reduce computational load, they often fail to capture the rich details, harmonics, and transient characteristics of real engine sounds, resulting in synthesized sounds that sound "mechanical" or "artificial," with lower fidelity than high-quality sampling.

[0005] Meanwhile, traditional synthesis / playback technologies focus primarily on the spectral characteristics of sound itself, but are not accurate enough in simulating the propagation of noise in three-dimensional space (such as attenuation, emission, and Doppler shift) and the binaural auditory localization of aircraft pilots (spatial audio), thus reducing the realism of the environment. Summary of the Invention

[0006] In view of the defects and shortcomings of existing technologies for sound simulation in flight simulators, which use sampling playback technology and physical modeling synthesis technology, this invention aims to provide a digital synthesis method for engine noise in flight simulators that combines high fidelity, high real-time performance, and smooth continuity. The method uses spectral difference analysis and dynamic filtering control to achieve engine noise synthesis, and directly extracts spectral features from real aircraft recordings to drive the synthesis process. The spectral target of the synthesized sound is derived from real data. While ensuring high fidelity of acoustic characteristics, the method reduces the computational complexity of synthesis and supports adaptation to new aircraft models by using an architecture of offline real aircraft data analysis and online real-time filtering synthesis, thereby improving the flexibility of the simulator sound system.

[0007] According to a first aspect of the present invention, a method for digitally synthesizing engine noise for an aircraft flight training simulator is provided, comprising the following steps: (1) In the offline analysis and preprocessing stage, by collecting audio samples of real aircraft engines under multiple different operating conditions and synchronously recording the corresponding engine operating parameters, a spectrum difference database of engine noise is constructed after performing spectrum analysis on the audio samples. (2) In the real-time audio rendering thread of the simulator host, the current engine operating parameters sent by the simulator host are received and interpolated and dynamically filtered in combination with the engine noise spectrum difference database, and the engine noise audio signal matching the spectrum characteristics of the current operating condition is output.

[0008] As an optional implementation, in step (1), the step of collecting audio samples of real aircraft engines under multiple different operating conditions and synchronously recording the corresponding engine operating parameters, and then constructing a spectrum difference database of engine noise after performing spectrum analysis on the audio samples, includes: S101: Collect audio samples of real aircraft engines under multiple different operating conditions and record the corresponding engine operating parameters simultaneously; S102: Perform spectral analysis on the audio samples to obtain the average spectrum or characteristic spectral envelope of the audio samples under each working condition; S103: Select the spectrum of the benchmark operating condition as the reference spectrum, calculate the spectrum difference between the spectrum of other operating conditions and the reference spectrum, and establish a mapping relationship table of engine core parameters and spectrum difference vector to form a spectrum difference database.

[0009] As an optional implementation, in step (2), in the real-time audio rendering thread of the simulator host, the current engine operating parameters sent by the simulator host are received and interpolated and dynamically filtered in combination with the engine noise spectrum difference database, and an engine noise audio signal matching the spectrum characteristics of the current operating condition is output, including the following steps: S201: Receive the current engine operating parameters sent by the simulator host in real time through the parameter interface, query the spectrum difference database based on the parameters as an index, and obtain the target spectrum difference vector corresponding to the current operating condition through interpolation calculation; S202: In the real-time audio rendering thread, a fundamental frequency noise signal is generated in real time. The fundamental frequency noise is pink noise or white noise, which has flat or known spectral characteristics. S203: Dynamically generate filter coefficients based on the target spectrum difference vector, and perform real-time dynamic filtering on the fundamental frequency noise signal to obtain the engine noise audio signal under the current operating conditions.

[0010] As an optional implementation, step (2) further includes S204: performing amplitude modulation on the signal after dynamic filtering, performing linear or nonlinear gain control based on engine thrust, so that the sound pressure level of the synthesized sound matches the power output of the real engine, and finally outputting it to the simulator audio system.

[0011] According to a second aspect of the present invention, a computer system is provided, comprising: One or more processors; The memory stores operable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations, including the aforementioned process for performing the digital synthesis method for engine noise of an aircraft flight training simulator.

[0012] In a third aspect of the present invention, a computer-readable medium for storing software is provided, the software including instructions executable by one or more computers, the instructions, when executed by the one or more computers, performing the process of the digital synthesis method for engine noise of an aircraft flight training simulator as described above.

[0013] The digital synthesis method for engine noise in aircraft flight training simulators described in the above embodiments of the present invention first drives the synthesis process by directly extracting spectral features from real aircraft recordings. The spectral target of the synthesized sound originates from real data, ensuring high fidelity of its acoustic characteristics and avoiding the "artificial" or "mechanical" timbre problems that may arise from pure algorithm modeling, enabling pilots to obtain credible auditory feedback. Based on this, a spectral difference database of engine noise is constructed through spectral analysis. Spectral difference interpolation is then performed on the real-time fundamental frequency noise signal (replacing traditional pre-recorded samples with malleable fundamental frequency noise), eliminating the inherent sound abruptness and repetition inherent in audio sampling and playback technology. By performing real-time, continuous interpolation calculations between spectral features under different operating conditions, it is ensured that the timbre and spectrum of the engine sound achieve a seamless and completely smooth transition as the throttle lever moves or other parameters change. This avoids the problems of sample repetition and transitional steps in sampling and playback, achieving infinite continuous variation of noise, thereby greatly enhancing the immersiveness of simulation training. It can be widely applied to civilian and special flight training simulators, UAV acoustic simulation platforms, and other transportation soundscape simulation systems.

[0014] Compared with the prior art, the significant advantages of the digital synthesis method for engine noise of aircraft flight training simulators of the present invention are as follows: (1) In the digital synthesis method for engine noise of aircraft flight training simulator proposed in this invention, the synthesis path for engine noise only includes digital signal processing operations for noise generation and filtering, and the computational complexity is much lower than that of complex physical modeling. At the same time, the system no longer uses a huge original audio sample library, but a refined and compressed spectral feature data table (such as standardized JSON / CSV). While realizing the quantitative correlation between engine parameters and acoustic features and providing data support for parameter driving during real-time synthesis, it significantly reduces the demand for hardware storage space and memory occupation, ensuring the stable operation of the system under high real-time requirements. At the same time, the standardized storage of the difference data table provides a flexible basis for subsequent adaptation to new aircraft models. Only the data table needs to be updated, without changing the core code. (2) The engine noise digital synthesis method of the present invention adopts a data-driven architecture. When it is necessary to configure the sound for a new model or a new engine, it is only necessary to re-execute the offline audio analysis and feature extraction process to generate a new spectrum database, without changing the core architecture and code of the real-time synthesis system, thereby improving the flexibility of the simulator sound system, reducing the adaptation cost and shortening the development cycle. (3) By incorporating the spectral characteristics under fault conditions into the spectral difference database, the system can respond to the fault signals sent by the simulator. By querying and applying special spectral difference vectors, it can dynamically synthesize sounds unique to abnormal operating conditions such as engine surge and stall, thereby realizing the ability to simulate abnormal operating conditions and providing key support for emergency response training.

[0015] It should be understood that all combinations of the foregoing concepts and the additional concepts described in more detail below may be considered part of the inventive subject matter of this disclosure, provided that such concepts do not contradict each other. Furthermore, all combinations of the claimed subject matter are considered part of the inventive subject matter of this disclosure.

[0016] The foregoing and other aspects, embodiments, and features of the teachings of the present invention will be more fully understood from the following description in conjunction with the accompanying drawings. Other additional aspects of the invention, such as features and / or beneficial effects of exemplary embodiments, will become apparent from the following description or may be learned through practice of specific embodiments according to the teachings of the present invention. Attached Figure Description

[0017] The accompanying drawings are not intended to be drawn to scale. In the drawings, each identical or nearly identical component shown in the various figures may be denoted by the same reference numeral. For clarity, not every component is labeled in each figure. Embodiments of various aspects of the invention will now be described by way of example and with reference to the accompanying drawings.

[0018] Figure 1 This is a flowchart illustrating a digital synthesis method for engine noise in an aircraft flight training simulator according to an embodiment of the present invention.

[0019] Figure 2 This is a schematic diagram of the principle of a digital synthesis system for engine noise of an aircraft flight training simulator according to an embodiment of the present invention.

[0020] Figure 3 This is a schematic diagram of another example of a digital synthesis system for engine noise of an aircraft flight training simulator according to an embodiment of the present invention. Detailed Implementation

[0021] To better understand the technical content of the present invention, specific embodiments are described below in conjunction with the accompanying drawings.

[0022] Various aspects of the invention are described in this disclosure with reference to the accompanying drawings, which illustrate numerous illustrative embodiments. The embodiments of this disclosure are not necessarily intended to encompass all aspects of the invention. It should be understood that the various concepts and embodiments described above, as well as those described in more detail below, can be implemented in any of many ways, because the concepts and embodiments disclosed herein are not limited to any particular implementation. Furthermore, some aspects of the invention disclosed may be used alone or in any suitable combination with other aspects of the invention disclosed.

[0023] Combination Figure 1 As shown, the digital synthesis method for engine noise of an aircraft flight training simulator according to an example of the present invention includes the following steps: (1) In the offline analysis and preprocessing stage, by collecting audio samples of real aircraft engines under multiple different operating conditions and synchronously recording the corresponding engine operating parameters, a spectrum difference database of engine noise is constructed after performing spectrum analysis on the audio samples. (2) In the real-time audio rendering thread of the simulator host, the current engine operating parameters sent by the simulator host are received and interpolated and dynamically filtered in combination with the engine noise spectrum difference database, and the engine noise audio signal matching the spectrum characteristics of the current operating condition is output.

[0024] As an optional implementation, in step (1), the step of collecting audio samples of real aircraft engines under multiple different operating conditions and synchronously recording the corresponding engine operating parameters, and then constructing a spectrum difference database of engine noise after performing spectrum analysis on the audio samples, includes: S101: Collect audio samples of real aircraft engines under multiple different operating conditions and record the corresponding engine operating parameters simultaneously; S102: Perform spectral analysis on the audio samples to obtain the average spectrum or characteristic spectral envelope of the audio samples under each working condition; S103: Select the spectrum of the benchmark operating condition as the reference spectrum, calculate the spectrum difference between the spectrum of other operating conditions and the reference spectrum, and establish a mapping relationship table of engine core parameters and spectrum difference vector to form a spectrum difference database.

[0025] In S101, on a real aircraft, measurement points covering all engine operating conditions are systematically selected to record engine audio signals, and the corresponding core engine parameters and flight parameters under these conditions are recorded simultaneously. The full-condition audio recording sampling of the actual aircraft covers the entire operating range, including at least different N1 / N2 speeds from idle to maximum thrust, different power lever angles (PLA), and different flight states (airspeed, altitude). Audio can be recorded from typical locations such as the cockpit and external cabin, ensuring the authenticity of the sound source. Simultaneously, through the aircraft data bus, the recorded audio signals are precisely correlated with real-time parameters such as N1 / N2, PLA, airspeed, and altitude, forming a raw dataset with a one-to-one correspondence between audio and parameters. This provides a real data source for subsequent spectral feature extraction, ensuring that the acoustic characteristics of the synthesized sound are consistent with those of a real engine, avoiding the artificiality issues of purely physical modeling from the source, and supporting noise synthesis for the simulator across all flight conditions.

[0026] For example, the audio recording sample set of CFM56 engine collected from a real Boeing 737 aircraft needs to cover multiple key operating conditions such as ground idling (N1=20%~30%), cruise (N1=80%~85%), and maximum takeoff thrust (N1=100%). The recording time for each operating condition is no less than 60 seconds, and the precise flight parameters such as N1, N2 engine speed, and airspeed are recorded simultaneously.

[0027] As an optional implementation, the spectrum difference database contains spectrum data of fault conditions. When the current engine operating parameters sent by the simulation host trigger an engine fault signal, the abnormal spectrum difference vector based on the fault condition is used to synthesize abnormal special situation sounds in the real-time audio rendering thread.

[0028] For example, when simulating engine surge, this invention can generate a sound that correlates speed fluctuations with abnormal spectrum changes in real time, while traditional technology can only play a fixed pre-recorded surge sound, resulting in a significant difference in realism.

[0029] In S102, the original dataset of audio parameters is imported, and time-frequency analysis is performed on each audio sample collected in S101 segment by segment. Short-time Fourier Transform (STFT) or Fast Fourier Transform is preferred to transform the audio signal in the time domain into the spectral features in the frequency domain. The feature curve is plotted with frequency as the horizontal axis and sound pressure level as the vertical axis. The analysis results are then processed to calculate the average spectrum or characteristic spectral envelope of each sample, thereby eliminating random noise interference in the audio, extracting the inherent spectral features of engine noise, and realizing the quantitative expression of sound features.

[0030] As an optional implementation, in S103, the ground idling state is selected as the baseline operating condition, and its average spectrum is used as the reference spectrum. The logarithmic frequency domain difference between the average spectrum of all other operating conditions and the reference spectrum is calculated to obtain the spectrum difference vector / filter response curve, thereby establishing a mapping relationship table between engine core parameters and spectrum difference vector, forming a spectrum difference database.

[0031] As an optional implementation, in step (2), in the real-time audio rendering thread of the simulator host, the current engine operating parameters sent by the simulator host are received and interpolated and dynamically filtered in combination with the engine noise spectrum difference database, and an engine noise audio signal matching the spectrum characteristics of the current operating condition is output, including the following steps: S201: Receives current engine operating parameters (such as N1 speed, PLA, Prop RPM, etc.) from the simulator host in real time via the parameter interface. The parameter mapping engine uses the received parameters as an index to query the spectrum difference database and calculates the target spectrum difference vector corresponding to the current operating condition through interpolation, outputting a continuous target spectrum difference vector. The interpolation algorithm can sample linear / bilinear interpolation, selected according to the parameter dimension. The parameter query interval is ≤20ms, synchronized with the simulation frame rate. In an optional embodiment, the speed of sound change can be controlled by interpolating the smoothing time constant (50ms~200ms) to simulate the inertia of an aircraft engine; S202: In the real-time audio rendering thread, a fundamental frequency noise signal is generated in real time. The fundamental frequency noise is pink noise or white noise, which has flat or known spectral characteristics. For example, pink noise (full-frequency characteristics, energy decreases by 1 / f as the frequency increases, close to the fundamental frequency characteristics of engine noise) is continuously generated according to the fixed sampling rate of the simulator audio, and the noise signal is continuously output to the dynamic filtering module, which is synchronized and parallel with the parameter query / interpolation processing of S201. S203: Dynamically generate filter coefficients based on the target spectrum difference vector, and perform real-time dynamic filtering on the fundamental frequency noise signal to obtain the engine noise audio signal under the current operating conditions.

[0032] Specifically, based on the target spectrum difference vector obtained by interpolation in S201, digital filter coefficients (preferably FIR filters, but IIR filters can also be used, with adjustable order from 128th to 512th order) are generated in real time. Then, through the dynamic filtering module, the digital filter is used to perform real-time filtering on the fundamental frequency noise signal generated in real time in S202 to obtain the target spectrum under the current operating conditions.

[0033] As an optional implementation, in S203, based on the received target spectrum difference vector, the digital filter coefficients are calculated and updated in real time according to the gain / attenuation values ​​of each frequency point in the vector, and the update frequency is synchronized with the query interval of S201; then, the baseband noise signal is input into the digital filter, and the digital filter performs precise gain / attenuation processing on the signals at different frequency points, so that the spectrum of the baseband noise signal forms a target spectrum of reference spectrum + current spectrum difference; after the filtering process is completed, an audio signal matching the spectrum characteristics of the current operating condition is output.

[0034] Thus, by filtering, the spectrum shaping from fundamental frequency noise to real engine noise is achieved, ensuring that the acoustic characteristics of the synthesized sound are highly consistent with those of the real engine. Furthermore, the filter coefficients are dynamically updated, allowing the noise spectrum to be adjusted in real time as flight parameters change continuously, achieving a stepless and smooth transition of engine noise and eliminating the gear effect of traditional sampling and playback.

[0035] As an optional implementation, step (2) further includes S204: performing amplitude modulation on the signal after dynamic filtering, performing linear or nonlinear gain control based on engine thrust, so that the sound pressure level of the synthesized sound matches the power output of the real engine, and finally outputting it to the simulator audio system or pilot headset.

[0036] In a specific example, the target sound pressure level is first determined based on the current engine thrust parameters (provided by the simulation host). Then, the gain of the filtered audio signal is controlled to adjust its amplitude to the target sound pressure level. Next, the signal is buffered and standardized to avoid issues such as popping and delay. Finally, the processed audio signal is output to the simulator's acoustic hardware (speakers or headphones) to complete the final noise synthesis. This ensures that the loudness of the synthesized noise precisely matches the engine's operating conditions, with higher loudness at maximum thrust and lower loudness at idle, enhancing the auditory realism and immersion. The process of digital synthesis of engine noise, as illustrated in the above example, is as follows: Figure 2 The example shown represents a schematic diagram of a digital synthesis system for engine noise in an aircraft flight training simulator, which includes a parameter interface module, a database module, an offline preprocessing module, and an online real-time synthesis module.

[0037] The parameter interface module is used to receive real-time flight parameters sent by the flight simulator host and perform standardized processing.

[0038] The offline preprocessing module is used to preprocess the audio samples of real aircraft engines under multiple different operating conditions (including different speeds, power lever angles and flight states) and the corresponding engine operating parameters recorded synchronously. This includes spectrum analysis and difference calculation based on the reference spectrum, establishing a mapping relationship table between engine core parameters and spectrum difference vectors, and forming a spectrum difference database.

[0039] The database module is used to store the reference spectrum and the spectrum difference database.

[0040] The online real-time synthesis module is used to perform difference query, fundamental frequency noise signal generation and dynamic filtering processing during flight simulator operation. Based on the current flight parameters, it dynamically shapes the spectrum of the fundamental frequency noise signal so that its spectrum is equal to the reference spectrum plus the current spectrum difference, thereby synthesizing a realistic engine noise signal under the current operating conditions.

[0041] The online real-time synthesis module includes a parameter mapping module, a noise generation module, and a dynamic filtering module.

[0042] The parameter mapping module is used to query and interpolate the spectral difference vector based on real-time flight parameters.

[0043] The noise generation module is used to generate fundamental frequency noise signals in real time, such as pink noise or white noise signals.

[0044] The dynamic filtering module is used to dynamically generate the coefficients of the digital filter based on the interpolated spectral difference vector, and to perform real-time filtering on the generated fundamental frequency noise signal.

[0045] In another embodiment, such as Figure 3 As shown, the online real-time synthesis module also includes an amplitude modulation module, which is used to adjust the amplitude of the filtered audio signal to match its overall sound pressure level with the current engine thrust level. Finally, the processed audio signal is output to the simulator's audio system or the pilot's headset, realizing a completely continuous and smooth transition of engine noise with changing operating conditions. Its dynamic change naturalness score is 35% higher on average than traditional multi-level sampling and playback technology, effectively eliminating the gear effect and repetition caused by sample switching, and greatly improving the immersive experience.

[0046] Meanwhile, the real-time synthesis core processing of this invention only involves noise generation and filtering, with extremely low computational load. Actual tests show that, on the same hardware platform, the CPU utilization of the audio synthesis thread of this invention is significantly lower than that of high-fidelity sampling playback and simplified physical modeling techniques, ensuring the high stability and reliability of the audio system when the simulator is running at full frame rate.

[0047] In conjunction with the above embodiments of the digital synthesis method for engine noise in aircraft flight training simulators, the present invention also discloses a computer system, comprising: One or more processors; Memory stores instructions that can be operated.

[0048] When the instructions are executed by the one or more processors, the one or more processors perform an operation, which includes the process of performing the digital synthesis method for engine noise of an aircraft flight training simulator as described in the foregoing embodiments.

[0049] In conjunction with the above embodiments of the digital synthesis method for engine noise of an aircraft flight training simulator, the present invention also discloses a computer-readable medium for storing software, the software including instructions executable by one or more computers.

[0050] When the instructions are executed by the one or more computers, they perform the process of the digital synthesis method for engine noise of an aircraft flight training simulator as described in the foregoing embodiments.

[0051] While the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the invention. Those skilled in the art can make various modifications and refinements without departing from the spirit and scope of the invention. Therefore, the scope of protection of the present invention shall be determined by the claims.

Claims

1. A method for digitally synthesizing engine noise for an aircraft flight training simulator, characterized in that, Includes the following steps: (1) In the offline analysis and preprocessing stage, by collecting audio samples of real aircraft engines under multiple different operating conditions and synchronously recording the corresponding engine operating parameters, a spectrum difference database of engine noise is constructed after performing spectrum analysis on the audio samples. (2) In the real-time audio rendering thread of the simulator host, the current engine operating parameters sent by the simulator host are received and interpolated and dynamically filtered in combination with the engine noise spectrum difference database, and the engine noise audio signal matching the spectrum characteristics of the current operating condition is output.

2. The method for digital synthesis of engine noise for an aircraft flight training simulator according to claim 1, characterized in that, In step (1), the process of collecting audio samples of real aircraft engines under multiple different operating conditions and simultaneously recording the corresponding engine operating parameters, and then constructing a spectrum difference database of engine noise after performing spectrum analysis on the audio samples, includes: S101: Collect audio samples of real aircraft engines under multiple different operating conditions and record the corresponding engine operating parameters simultaneously; S102: Perform spectral analysis on the audio samples to obtain the average spectrum or characteristic spectral envelope of the audio samples under each working condition; S103: Select the spectrum of the benchmark operating condition as the reference spectrum, calculate the spectrum difference between the spectrum of other operating conditions and the reference spectrum, and establish a mapping relationship table of engine core parameters and spectrum difference vector to form a spectrum difference database.

3. The method for digital synthesis of engine noise for an aircraft flight training simulator according to claim 2, characterized in that, The spectrum difference database contains spectrum data of fault conditions. When the current engine operating parameters sent by the simulation host trigger an engine fault signal, the abnormal spectrum difference vector based on the fault condition is used to synthesize abnormal special situation sounds in the real-time audio rendering thread.

4. The method for digital synthesis of engine noise for an aircraft flight training simulator according to claim 2, characterized in that, In S103, the ground idling state is selected as the baseline operating condition, and its average spectrum is used as the reference spectrum. The logarithmic frequency domain difference between the average spectrum of all other operating conditions and the reference spectrum is calculated to obtain the spectrum difference vector / filter response curve. Thus, a mapping relationship table between engine core parameters and spectrum difference vector is established, forming a spectrum difference database.

5. The method for digital synthesis of engine noise for an aircraft flight training simulator according to any one of claims 1 to 4, characterized in that, In step (2), in the real-time audio rendering thread of the simulator host, the current engine operating parameters sent by the simulator host are received and interpolated and dynamically filtered in combination with the engine noise spectrum difference database, and the engine noise audio signal matching the spectrum characteristics of the current operating condition is output, including the following steps: S201: Receive the current engine operating parameters sent by the simulator host in real time through the parameter interface, query the spectrum difference database based on the parameters as an index, and obtain the target spectrum difference vector corresponding to the current operating condition through interpolation calculation; S202: In the real-time audio rendering thread, a fundamental frequency noise signal is generated in real time. The fundamental frequency noise is pink noise or white noise, which has flat or known spectral characteristics. S203: Dynamically generate filter coefficients based on the target spectrum difference vector, and perform real-time dynamic filtering on the fundamental frequency noise signal to obtain the engine noise audio signal under the current operating conditions.

6. The method for digital synthesis of engine noise for an aircraft flight training simulator according to claim 5, characterized in that, Step (2) also includes S204: Amplitude modulation of the signal after dynamic filtering, linear or nonlinear gain control based on engine thrust, so that the sound pressure level of the synthesized sound matches the power output of the real engine, and finally outputs it to the simulator audio system.

7. The method for digital synthesis of engine noise for an aircraft flight training simulator according to claim 5, characterized in that, In S203, based on the received target spectrum difference vector, the digital filter coefficients are calculated and updated in real time according to the gain / attenuation values ​​of each frequency point in the vector, and the update frequency is synchronized with the query interval of S201; then the baseband noise signal is input into the digital filter, and the digital filter performs precise gain / attenuation processing on the signals at different frequency points, so that the spectrum of the baseband noise signal forms the target spectrum of the reference spectrum plus the current spectrum difference; after the filtering process is completed, an audio signal matching the spectrum characteristics of the current operating condition is output.

8. The method for digital synthesis of engine noise for an aircraft flight training simulator according to claim 7, characterized in that, The digital filter is an FIR filter or an IIR filter, with an adjustable order from 128th to 512th.

9. A computer system, characterized in that, include: One or more processors; A memory that stores operable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations, including the process of performing the digital synthesis method for engine noise of an aircraft flight training simulator according to any one of claims 1-8.

10. A computer-readable medium for storing software, characterized in that, The software includes instructions executable by one or more computers, which, when executed by the one or more computers, perform the process of the digital synthesis method for engine noise of an aircraft flight training simulator as described in any one of claims 1-8.

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