A reflective fiber turbine oxygen supply flow detection and avionics conversion system and method

Abstract

The application relates to a reflective optical fiber turbine oxygen supply flow detection and avionics conversion system and method, and belongs to the technical field of airborne oxygen supply detection and avionics bus. The system comprises the following: an optical fiber turbine oxygen supply flow detection unit, which is used for rectifying the oxygen supply airflow to be detected and then conveying the airflow to a turbine to drive the turbine to rotate, and collecting a periodic light pulse signal generated by the rotation of the turbine; a signal processing and conversion unit, which is used for converting the periodic light pulse signal into a voltage pulse signal and performing hierarchical processing, and obtaining a calibrated pulse signal after waveform shaping and proportional scaling; a bus conversion unit, which is used for measuring the frequency of the calibrated pulse signal, calculating an instantaneous oxygen supply flow value and converting the value into an ARINC429 protocol data frame; and a driving differential output circuit, which is used for converting the ARINC429 protocol data frame into a differential electrical signal of bipolar return-to-zero code and outputting the signal to an avionics bus network. The application can meet the urgent needs of high-performance aircraft for intelligentization and high reliability of an oxygen supply system.

Description

Technical Field

[0001] This application relates to the field of airborne oxygen supply detection and avionics bus technology, and in particular to a reflective fiber optic turbine oxygen supply flow detection and avionics conversion system and method. Background Technology

[0002] Modern military and civilian aircraft have increasingly stringent requirements for flight safety. As a critical life support subsystem, the pilot oxygen supply system's real-time monitoring accuracy and reliability directly affect the pilot's survival safety and mission performance.

[0003] Currently, commonly used airborne oxygen supply flow detection solutions are mainly based on mechanical impellers, Hall effect sensing, or differential pressure measurement principles. These traditional technical solutions can meet basic requirements under normal flight conditions, but as the flight envelope of aircraft continues to expand (such as in extreme conditions such as supersonic cruise, high-G maneuvers, and high-altitude low-pressure environments), these methods still have many inherent defects.

[0004] First, mechanical flow sensors rely on physical contact transmission between the impeller rotation and the electromagnetic induction element. The inherent inertia and frictional resistance of the mechanical transmission mechanism cause a significant hysteresis in the sensing system's response to instantaneous changes in oxygen flow. This hysteresis effect directly affects the real-time performance of the measurement data during rapid flow fluctuations (such as a pilot's sudden change in breathing requirements), making it difficult to accurately capture instantaneous flow.

[0005] Secondly, electromagnetic sensing elements (such as Hall sensors) widely used in traditional solutions face severe challenges in the complex electromagnetic environment of airborne systems. The dense radio frequency radiation, high-power radar pulses, and electrical load switching noise of aircraft electronic systems can easily interfere with sensing signals through electromagnetic coupling, causing measurement data distortion, false triggering, or intermittent failures. In severe cases, this may lead to false alarms or incorrect control commands.

[0006] Furthermore, at the system integration level, the output signals of existing flow detection devices are mostly non-standard analog quantities (such as voltage / current) or raw pulse signals, which cannot be directly compatible with the standardized digital bus protocols commonly used in modern avionics systems. This forces aircraft system designs to add extra signal conditioning modules, protocol converters, and interface circuits, objectively increasing system weight, wiring complexity, and potential fault points. Especially in high-density integrated avionics architectures, the latency and compatibility issues caused by multi-level signal conversion have become one of the bottlenecks restricting the intelligent upgrade of oxygen supply systems. Summary of the Invention

[0007] To meet the urgent need for intelligent and highly reliable oxygen supply systems in high-performance aircraft, this application provides a reflective fiber optic turbine oxygen supply flow detection and avionics conversion system and method.

[0008] In a first aspect, this application provides a reflective fiber optic turbine oxygen supply flow detection and avionics conversion system, which adopts the following technical solution:

[0009] A reflective fiber optic turbine oxygen supply flow detection and avionics conversion system, the system comprising:

[0010] The fiber optic turbine oxygen supply flow detection unit is used to rectify the oxygen supply flow to be detected and then send it to the turbine to drive the turbine to rotate, and to collect the periodic optical pulse signal generated by the rotation of the turbine.

[0011] The signal processing and conversion unit is used to convert the periodic optical pulse signal into a voltage pulse signal and perform hierarchical processing. After waveform shaping and scaling, a calibration pulse signal is obtained.

[0012] The bus conversion unit is used to measure the frequency of the calibration pulse signal, calculate the instantaneous oxygen supply flow rate, and convert the instantaneous oxygen supply flow rate into an ARINC429 protocol data frame.

[0013] The differential output circuit is used to convert the ARINC429 protocol data frame into a bipolar return-to-zero code differential electrical signal and output it to the avionics bus network.

[0014] By adopting the above technical solutions, high-precision, real-time online monitoring of oxygen supply flow has been achieved, and standardized data docking with avionics systems has been completed, which can meet the stringent requirements of modern aircraft for intelligent, integrated, and highly reliable life support systems.

[0015] Secondly, this application provides a method for detecting oxygen supply flow rate and converting avionics using a reflective fiber optic turbine, employing the following technical solution:

[0016] A method for detecting and converting oxygen supply flow rate of a reflective fiber optic turbine into avionics components, applied to the reflective fiber optic turbine oxygen supply flow rate detection and avionics conversion system described in the first aspect; the method includes:

[0017] The oxygen supply flow to be tested is rectified and then sent to the turbine to drive the turbine to rotate, and the periodic light pulse signal generated by the turbine rotation is collected.

[0018] The periodic optical pulse signal is converted into a voltage pulse signal and processed in stages. After waveform shaping and scaling, a calibration pulse signal is obtained.

[0019] The frequency of the calibration pulse signal is measured, the instantaneous oxygen supply flow rate is calculated, and the instantaneous oxygen supply flow rate is converted into an ARINC429 protocol data frame.

[0020] The ARINC429 protocol data frame is converted into a bipolar return-to-zero code differential electrical signal and output to the avionics bus network.

[0021] In summary, this application includes at least one of the following beneficial technical effects: Through a collaborative "optical-mechanical-electronic" design, it achieves non-contact, high-precision, and rapid response detection of oxygen supply flow, possesses excellent electromagnetic compatibility and environmental adaptability, and solves the performance degradation problem of traditional mechanical sensors under extreme conditions. Simultaneously, by directly outputting ARINC429 signals through the FPGA's built-in protocol soft core, it achieves plug-and-play integration with the avionics system, providing a continuous, reliable, and standardized oxygen supply data stream for the flight control system. This system not only meets the stringent requirements of modern aircraft for high reliability and real-time performance in life support systems, but also provides a solid data foundation and technical support for the future realization of intelligent on-demand oxygen supply closed-loop control based on physiological parameter feedback. Attached Figure Description

[0022] Figure 1 This is a structural block diagram of a reflective fiber optic turbine oxygen supply flow detection and avionics conversion system according to one embodiment of this application.

[0023] Figure 2 This is a schematic diagram of the structure of a fiber optic turbine oxygen supply flow detection unit according to one embodiment of this application.

[0024] Figure 3 This is a circuit structure diagram of a photoelectric conversion circuit according to one embodiment of this application.

[0025] Figure 4 This is a circuit structure diagram of a waveform shaping circuit according to one embodiment of this application.

[0026] Figure 5 This is a circuit diagram of a scaling circuit according to one embodiment of this application.

[0027] Figure 6 This is a schematic diagram of the first process of a method for detecting oxygen supply flow rate and converting avionics using a reflective fiber optic turbine, according to one embodiment of this application.

[0028] Figure 7 This is a schematic diagram of the second process of a method for detecting oxygen supply flow rate and converting avionics using a reflective fiber optic turbine, according to one embodiment of this application.

[0029] Explanation of reference numerals in the attached drawings: 1. Housing; 2. Flow guide; 3. Turbine assembly; 31. Shaft; 32. Bearing; 33. Blade; 34. Reflector; 4. Reflective fiber optic sensor; 41. Y-type fiber optic assembly; 42. Optical lens; 5. Oxygen inlet; 6. Oxygen outlet; 7. Optical transceiver assembly. Detailed Implementation

[0030] To make the purpose, technical solution, and advantages of this application clearer, the following description is provided in conjunction with the appendix. Figure 1-7 The present application will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the application.

[0031] Currently, existing technologies generally employ impellers, Hall effect sensors, or differential pressure sensors for flow monitoring. These mechanical structures suffer from inertia and friction, resulting in slow response to flow changes and difficulty in accurately capturing instantaneous flow. Furthermore, electromagnetic sensing methods are susceptible to the complex electromagnetic environment of airborne systems, causing signal distortion or even failure. In addition, moving parts are prone to wear and jamming during long-term operation, leading to a high risk of failure under vibration and shock conditions and high maintenance costs. Moreover, these sensors often output analog or non-standard digital signals, requiring multiple conversion stages before connecting to standard avionics buses such as ARINC429. This not only increases system complexity, weight, and potential failure points but also hinders the development of modern aircraft's demand for highly integrated and intelligent control of oxygen supply systems.

[0032] Based on this, this application discloses a reflective fiber optic turbine oxygen supply flow detection and avionics conversion system.

[0033] Reference Figure 1 A reflective fiber optic turbine oxygen supply flow detection and avionics conversion system, the system comprising:

[0034] The fiber optic turbine oxygen supply flow detection unit is used to rectify the oxygen supply flow to be detected and then send it to the turbine to drive the turbine to rotate, and to collect the periodic optical pulse signal generated by the turbine rotation.

[0035] The signal processing and conversion unit is used to convert periodic optical pulse signals into voltage pulse signals and perform hierarchical processing. After waveform shaping and scaling, a calibration pulse signal is obtained.

[0036] The bus conversion unit is used to measure the frequency of the calibration pulse signal, calculate the instantaneous oxygen supply flow rate, and convert the instantaneous oxygen supply flow rate into ARINC429 protocol data frames;

[0037] The differential output circuit is used to convert ARINC429 protocol data frames into differential electrical signals of bipolar return-to-zero code and output them to the avionics bus network.

[0038] In the above embodiments, non-contact optical sensing is achieved through a fiber optic turbine unit, converting the mechanical motion of airflow driving turbine rotation into periodic optical pulse signals. This fundamentally eliminates the wear and inertial delay caused by traditional mechanical contact, significantly improving measurement accuracy and response speed. The signal processing and conversion unit performs photoelectric conversion, shaping, and hardware-level scaling on the optical pulses, ensuring the accuracy and real-time performance of the flow data. The bus conversion unit, based on FPGA high-precision frequency measurement and integrating the ARINC429 protocol soft core, completes the digital processing and standard frame encapsulation of the flow data. Finally, the drive differential output circuit converts the data into a bipolar return-to-zero code differential signal conforming to aviation specifications, directly connecting it to the avionics bus network. The entire system achieves high precision, high reliability, and strong anti-electromagnetic interference capability for oxygen supply flow detection, and supports seamless integration with the aircraft avionics system, providing a stable and standardized data foundation for intelligent oxygen supply control.

[0039] Reference Figure 2 As one implementation of the fiber optic turbine oxygen supply flow detection unit, the fiber optic turbine oxygen supply flow detection unit includes a housing 1, a flow guide 2, a turbine assembly 3, and a reflective fiber optic sensor 4.

[0040] The flow guide 2 is fixedly installed inside the oxygen inlet 5 of the housing 1, and is used to rectify the oxygen supply flow to be tested into an axial airflow.

[0041] The turbine assembly 3 includes a rotating shaft 31 rotatably disposed within the housing 1 and blades 33 covered with reflectors 34. The rotating shaft 31 is coaxially fixed to the guide vane 2 via a bearing 32, and the blades 33 are fixedly disposed on the rotating shaft 31. The blades 33 are used to rotate under the push of axial airflow.

[0042] The reflective fiber optic sensor 4 includes a Y-shaped fiber optic assembly 41, a light source, and an optical lens 42. The optical lens 42 is disposed at the end of the Y-shaped fiber optic assembly 41 and is used to collimate the emitted light beam and focus the reflected light signal. The emitting branch of the Y-shaped fiber optic assembly 41 is used to emit a light beam from the light source to the blade 33, and the receiving branch is used to capture the light pulse signal periodically reflected by the reflector 34 of the blade 33.

[0043] In the mechanical structure, the housing 1 serves as the main structure and protective shell of the entire detection unit. It not only provides an installation reference for each component but also possesses excellent airtightness, effectively isolating external environmental interference and ensuring stable internal airflow. The flow guide 2, located after the oxygen inlet 5, is used to rectify and optimize the incoming oxygen flow, eliminating eddies and radial velocity components generated during intake, forming a uniform and stable axial airflow. This improves the interaction efficiency between the airflow and the turbine blades 33, enhancing measurement accuracy. The bearing 32, as the high-speed rotating support mechanism of the turbine assembly 3, provides high-precision, low-friction rotational support for the turbine, ensuring its sensitive and free rotation during operation, converting fluid kinetic energy into mechanical rotational motion without lag. The turbine assembly 3 contains multiple blades 33, which are the core components for converting fluid kinetic energy into mechanical energy. When oxygen flows through the blades 33, it drives the turbine to rotate. The turbine's rotational speed is strictly linearly proportional to the oxygen flow velocity, thus converting the flow velocity information into a measurable rotational signal.

[0044] Meanwhile, a reflector 34 is provided on the end face of each blade 33 as a reflective surface required for subsequent optical detection. The oxygen inlet 5 and the oxygen outlet 6 serve as the inlet and outlet channels for the oxygen supply flow, respectively, guiding oxygen into and out of the detection unit to form a complete measurement flow channel and maintain the continuity and stability of the airflow.

[0045] In the optical detection section, a Y-shaped fiber optic assembly is used to achieve optical path transmission and separation. One transmitting branch transmits the emitted light from the light source to the turbine region, while the other receiving branch receives the light signal reflected back from the blade 33. This achieves physical isolation and integration of the transmitting and receiving optical paths, avoiding optical crosstalk. The optical transceiver assembly 7 consists of a light-emitting diode (LED) and a photodiode. The LED provides a stable and continuous light source, illuminating the end face of the turbine blade 33; the photodiode receives the periodically changing reflected light signal and converts it into a corresponding electrical pulse signal, completing the crucial conversion process from optical signal to electrical signal. An optical lens 42 is positioned between the light source and the optical fiber to collimate and focus the light beam emitted by the LED, ensuring efficient coupling into the transmitting fiber and concentrated transmission of light energy.

[0046] In this embodiment, the optical lens 42 is a cemented doublet lens with a diameter of 4mm, made of two pieces of optical glass of different materials bonded together. It can effectively correct spherical aberration and chromatic aberration, significantly improve focusing accuracy and imaging quality, and ensure the stability of the optical path system. The reflector 34 is attached to the end face of each blade 33 of the turbine, forming a highly reflective observation surface. It can periodically and efficiently reflect the incident light back to the receiving optical fiber during the rotation of the blade 33, providing a stable and clear signal source for optical detection.

[0047] Based on the above structure, when the fiber optic turbine oxygen supply flow detection unit is connected to the airborne oxygen supply pipeline system, oxygen flows into the detection unit at high speed from the oxygen inlet 5. First, the airflow is rectified and optimized by the flow guide 2, eliminating eddies and radial velocity components during the intake process, forming a uniformly distributed and directionally stable axial airflow. This stable airflow acts on the surface of the turbine blades 33, generating a continuous axial thrust, driving the turbine assembly 3 to rotate around its main shaft. According to the principles of energy conversion and momentum transfer in fluid mechanics, the rotational kinetic energy obtained by the turbine originates from the conversion of oxygen flow energy. Under design conditions, there is a significant linear positive correlation between the turbine speed and the oxygen flow velocity: that is, the greater the airflow velocity, the higher the momentum increment impacting the blades 33 per unit time, and the stronger the driving torque generated, thus leading to a corresponding increase in turbine speed. The turbine assembly 3 is supported inside the housing 1 by a high-precision bearing 32. This bearing 32 has the characteristics of low friction and high rotational accuracy, ensuring that the turbine can rotate sensitively and freely, realizing the seamless conversion of fluid flow velocity into mechanical rotational motion.

[0048] To achieve non-contact, precise measurement of the mechanical rotation parameters, the system employs reflective fiber optic sensing technology. A dedicated reflector 34 with high reflectivity is attached to the end face of each turbine blade 33, forming a highly efficient and stable optical reflective surface. The Y-shaped fiber optic assembly 41 and the optical transceiver assembly 7 together constitute the reflective fiber optic sensor 4. The transmitting fiber projects a beam of light from a stable light source onto the detection area along the rotation path of the turbine blade 33, while the receiving fiber collects the light signals periodically reflected back by the reflector 34. As the turbine rotates, each blade 33 passes through the beam illumination area sequentially. Whenever the end face of a blade 33 with the highly reflective reflector 34 enters the detection area, the incident light is efficiently reflected and coupled into the receiving fiber. When the blade 33 rotates away or is in a non-reflective position, the reflected signal is interrupted, and the received light intensity is significantly reduced.

[0049] Therefore, for each complete rotation of the turbine, the receiver generates a periodic optical pulse signal that strictly corresponds to the number of blades (33). By counting and analyzing the frequency of this optical pulse signal, the real-time turbine rotation speed can be accurately obtained, and the instantaneous oxygen flow rate can be calculated by combining the linear relationship between flow velocity and rotation speed. This optical detection method achieves non-contact measurement, completely avoiding the wear and jamming risks associated with traditional mechanical contact, while also possessing excellent anti-electromagnetic interference capabilities, making it suitable for applications in complex electromagnetic environments and high reliability requirements of aircraft.

[0050] In terms of optical system structure design, this application adopts a Y-branch-based multimode fiber structure as the optical path transmission and separation device. One branch serves as the transmitting fiber, and the other branch serves as the receiving fiber, achieving a high degree of integration and effective isolation of the transmitting and receiving optical paths in physical space. To maximize the system's light energy utilization, the coupling efficiency between the light source and the fiber needs to be precisely controlled: the light beam emitted by the light-emitting diode is collimated and focused using an optical lens 42, and the fiber end face is precisely fixed at the focal plane of the lens to ensure that the light energy of maximum intensity is efficiently coupled into the transmitting fiber, thereby providing a sufficient and stable initial optical signal for subsequent optical detection. Since the fiber length used in the detection unit is extremely short, the optical signal attenuation during transmission is negligible. Therefore, the signal quality of the entire system mainly depends on the coupling efficiency of the front-end optical path. The optimized coupling design significantly improves the signal-to-noise ratio, ensures the intensity and waveform clarity of the reflected light signal, and provides a reliable foundation for subsequent photoelectric conversion and pulse signal processing.

[0051] To further achieve high-intensity, low-loss transmission of optical signals, the optical system design focuses on two core aspects: efficient light source-fiber coupling and strict control of the light incident angle. Specifically, the light beam emitted by the light source is collimated and focused by a 4mm diameter cemented doublet lens to form a parallel beam with concentrated direction and stable energy, which is then efficiently guided into the transmitting fiber. This cemented doublet lens is made of two pieces of optical glass of different materials cemented together, which can effectively correct the spherical aberration and chromatic aberration inherent in a single lens, significantly improving focusing accuracy and imaging quality, and ensuring that the beam accurately converges at the target position.

[0052] Furthermore, to meet the conditions for total internal reflection transmission within the optical fiber, the incident angle of the light must be strictly controlled. The angle from the light source to the transmitting fiber, and the angle of incidence after reflection by blade 33 into the receiving fiber, must not exceed 12°. This prevents leakage or dissipation of the optical signal during transmission, ensuring that the light energy is confined to the fiber to the maximum extent possible, ultimately guaranteeing a sufficiently strong reflected light signal at the receiving end. After precise adjustment and determination of the optimal optical path position, the lenses are firmly bonded to the probe housing 1 using a special optical adhesive. This fixing method not only provides good shock resistance and temperature adaptability but also ensures the long-term stability and reliability of the entire optical system.

[0053] At the signal receiving end, the system is equipped with a photoelectric conversion module based on a photodiode to efficiently convert the received periodic reflected light signal into a weak pulsed current signal. This electrical signal is then sent to an amplification and conditioning circuit, where it undergoes amplitude amplification and noise filtering to form a regular and clear pulsed voltage waveform. The conditioned signal is then sent to a counter for precise pulse accumulation and frequency calculation. Finally, the oxygen flow rate is calculated based on the linear relationship between the pulse frequency and the fluid flow rate, with the mathematical expression: Q = K·N;

[0054] Where Q represents oxygen flow rate, N represents pulse frequency per unit time (proportional to turbine speed), and K is a preset proportionality coefficient.

[0055] It should be noted that this preset proportional coefficient is a key calibration parameter of the sensor system. Its value comprehensively reflects the quantitative mapping relationship between the geometric structural characteristics of the turbine assembly 3 and its hydrodynamic behavior. It is mainly determined by structural parameters such as the angle between the turbine blade 33 and the main shaft axis (i.e., the inclination angle of the turbine blade 33), the average rotational radius of the turbine, and the cross-sectional area of ​​the flow channel where the turbine is located. These parameters directly affect the torque exerted by the airflow on the blade 33 and the rotational inertia of the turbine, thus determining the conversion characteristics between rotational speed and flow velocity. Therefore, the preset proportional coefficient K essentially constitutes a quantitative bridge connecting the mechanical output of the sensor and the optical detection results, and is the core calibration factor for achieving accurate conversion of physical motion quantities into electrical output quantities.

[0056] This application achieves oxygen flow measurement through a precise opto-mechanical-electronic collaborative mechanism: After oxygen enters through the oxygen inlet 5, it first passes through the guide vane 2 to form a stable axial airflow, and then drives the turbine assembly 3 to rotate at high speed around the bearing 32. The turbine speed is strictly linearly proportional to the oxygen flow rate, realizing the effective conversion of fluid kinetic energy into mechanical rotational kinetic energy. The reflector 34 attached to the end face of the blade 33 rotates synchronously with the turbine, periodically modulating the light beam emitted by the Y-shaped optical fiber to form a light pulse sequence related to the rotational speed. The reflected light is transmitted to the photodiode through the receiving optical fiber to complete the photoelectric conversion. The generated electrical pulse signal is further sent to the subsequent signal processing circuit for amplification, shaping, and frequency calculation. Finally, the actual oxygen flow value is calculated according to the preset proportional coefficient K. The above components cooperate and work together to ensure the high precision, high response speed, and long-term reliability of the detection unit in the extreme aviation environment, laying a solid foundation for the stable operation of the entire oxygen flow detection and avionics bus conversion system.

[0057] Reference Figure 1 As one implementation of the signal processing and conversion unit, the signal processing and conversion unit includes a photoelectric conversion circuit, a waveform shaping circuit, and a scaling circuit.

[0058] The photoelectric conversion circuit includes a photodiode and an operational amplifier; the photodiode converts periodic light pulse signals into current signals; the operational amplifier amplifies and filters the current signal into voltage pulse signals through a transimpedance amplifier circuit composed of a feedback resistor and a parallel capacitor.

[0059] The waveform shaping circuit is used to receive voltage pulse signals, eliminate signal jitter by hysteresis voltage comparison, and output a standard square wave signal.

[0060] The scaling circuit receives a standard square wave signal and a binary encoded value of a preset scaling factor, scales the number of pulses proportionally, and outputs a calibration pulse signal.

[0061] In the above embodiment, the signal processing and conversion unit adopts a hierarchical processing mode to condition and calculate the optical signal from the fiber optic sensing section step by step to achieve high-precision and high-stability oxygen flow rate data output. This unit first receives the weak photocurrent signal output by the photodiode through a photoelectric conversion circuit, converts it into a voltage signal, and amplifies it; then, a waveform shaping circuit completes waveform regularization, outputting a standard digital square wave; finally, a scaling circuit performs real-time scaling of the pulse frequency according to a preset flow rate calibration coefficient K to obtain an output signal corresponding to the actual oxygen flow rate. These three circuits are sequentially connected and work collaboratively, completely covering the entire process from raw optical signal acquisition to accurate flow rate calculation, ensuring stable and reliable signal processing even in complex aviation environments.

[0062] Reference Figure 3 The photoelectric conversion circuit is the primary processing module of the signal processing and conversion unit, responsible for converting the periodic light pulse signals generated by the optical detection stage into processable electrical signals. Specifically, the photoelectric conversion circuit includes a first resistor R1, a second resistor R2, a third resistor R3, a fourth resistor R4, a fifth resistor R5, a sixth resistor R6, a first capacitor C1, a second capacitor C2, a third capacitor C3, a fourth capacitor C4, a photodiode D1, a first potentiometer PR1, and an operational amplifier IC1. The operational amplifier IC1 uses a low-drift general-purpose integrated operational amplifier uA741 as the core component to construct a transimpedance amplification structure, achieving high-precision linear conversion of weak photocurrents. The cathode of the photodiode D1 is connected to the non-inverting input of the operational amplifier IC1, while the anode is grounded through the second resistor R2 and the first capacitor C1, forming a bias circuit. This connection method allows the photodiode to operate in near-zero bias photovoltaic mode, fully utilizing the high input impedance characteristics of the operational amplifier, effectively reducing the influence of dark current and junction capacitance, thereby improving its response speed and linearity to changes in weak illumination.

[0063] To ensure stable operation of operational amplifier IC1 within its optimal linear range, the circuit employs a ±12V symmetrical dual power supply structure. The positive power supply terminal of operational amplifier IC1 is connected to the +12V power supply and one end of the third capacitor C3, with the other end of capacitor C3 grounded. The negative power supply terminal is connected to the -12V power supply and one end of the second capacitor C2, with the other end of capacitor C2 grounded. This dual power supply configuration provides ample dynamic output range, avoids signal clipping at the bottom that may occur with a single power supply, and significantly enhances the stability and reliability of the circuit during linear amplification.

[0064] To further improve DC accuracy and zero-point stability under small-signal conditions, a zero-adjustment mechanism is introduced at the external input offset voltage adjustment terminal of operational amplifier IC1. Specifically, a precision potentiometer RP1 is connected externally between the first and second external input offset voltage adjustment terminals of IC1. The two fixed terminals of RP1 are connected to the two adjustment terminals respectively, and the sliding terminal is connected to the positive power supply terminal. By adjusting the position of the sliding contact of RP1, a compensation voltage equal in magnitude but opposite in direction to the inherent input offset voltage of the op-amp can be generated internally, thereby effectively offsetting the DC offset caused by input stage transistor mismatch and ensuring that the zero-point drift of the system is controlled within the allowable range during long-term operation.

[0065] For signal amplification, the feedback network consists of a fourth resistor R4 and a sixth resistor R6 connected in series and a fourth capacitor C4 connected in parallel, and is connected between the inverting input and output of operational amplifier IC1. The first resistor R1 is connected between the inverting input and ground to set the reference level. This structure constitutes a composite feedback path with gain control. The overall voltage amplification factor is determined by the formula A = 1 + (R4 + R6) / R1. Based on the actual parameter values, when R4 is 1MΩ, R6 is 100kΩ, and R1 is 100kΩ, the calculated amplification factor is: A = 1 + 1.1 MΩ / 100 kΩ = 12, achieving effective amplification of the weak photocurrent.

[0066] Furthermore, the fourth capacitor C4 (0.1μF) connected in parallel in the feedback loop and the fourth resistor R4 together form a first-order RC low-pass filter network, whose cutoff frequency is given by the formula f. c =1 / (2πRC) is determined. This filter structure can effectively suppress high-frequency noise interference, smooth the output waveform, and prevent false triggering caused by external electromagnetic disturbances or optical signal jitter while realizing the signal amplification function, ensuring that only one clear and stable electrical pulse is output for each rotation of the turbine.

[0067] Furthermore, the output of operational amplifier IC1 is connected to one end of the fifth resistor R5, and the other end of the fifth resistor R5 serves as the output terminal U_A of the entire photoelectric conversion circuit, providing an amplified and filtered analog voltage signal to the subsequent Schmitt trigger shaping circuit. When the turbine assembly 3 rotates under the propulsion of the airflow, the high-reflectivity film on the end face of the blades 33 periodically reflects the incident light, forming a light pulse sequence consistent with the number of blades 33. This light pulse is received by the photodiode D1 and converted into a corresponding photocurrent. This photocurrent is then converted to voltage, amplified, and filtered by this stage of the circuit, forming a voltage pulse signal at the output terminal U_A that precisely corresponds to changes in light intensity. By counting the frequency of this pulse sequence, the turbine speed can be accurately reflected, and further combined with the instrument coefficient to calculate the instantaneous oxygen flow rate.

[0068] Based on this, the photoelectric conversion circuit achieves high sensitivity, high signal-to-noise ratio, and high linearity conversion and amplification of weak light signals by adopting dual power supply, photodiode connected to the non-inverting terminal, external potentiometer zeroing, RC composite feedback amplification and filtering, etc., providing a high-quality pre-amplifier signal foundation for subsequent digital signal processing, and is one of the key links to ensure the measurement accuracy and reliability of the entire system.

[0069] Reference Figure 4 As one implementation of a waveform shaping circuit, the waveform shaping circuit employs a Schmitt trigger shaper, specifically including:

[0070] The fifth capacitor has one end connected to the output terminal of the photoelectric conversion circuit;

[0071] A Schmitt trigger consists of two inverter stages; the input of the first inverter is connected to the other end of the fifth capacitor, the output of the first inverter is connected to the input of the second inverter, and the output of the second inverter is used to generate a standard square wave signal.

[0072] In this embodiment, the Schmitt trigger circuit functions to shape and suppress noise in the analog pulse signal output from the preceding photoelectric conversion circuit, generating a standard square wave signal that meets the input requirements of the digital circuit. The input of this circuit is connected to the output U_A of the photoelectric conversion circuit, and AC coupling is achieved through the fifth capacitor C5. This filters out any DC components or low-frequency drift that may be superimposed on the signal, ensuring that only valid pulse signals are transmitted to subsequent processing units. One end of the fifth capacitor C5 is connected to U_A, and the other end is connected to the input of the first channel inverter IC2_1 in the Schmitt trigger IC2. This inverter performs the initial shaping operation on the input signal; its output is further connected to the input of the second channel inverter IC2_2 of the Schmitt trigger. After secondary shaping, the output of IC2_2 is U_B, which is then transmitted to the proportional multiplier circuit as the clock input for subsequent flow calculation.

[0073] Specifically, this circuit integrates a six-channel Schmitt trigger chip as the core device, utilizing its built-in hysteresis voltage characteristic to effectively process irregular waveforms. Since the pulse signal output from the preamplifier may exhibit edge jitter, glitches, or amplitude fluctuations in actual operating environments, directly using it for digital counting or frequency measurement can easily lead to false triggering, over-counting, or under-counting problems. Therefore, the Schmitt trigger IC2 establishes a hysteresis range (i.e., hysteresis voltage) for the input voltage by setting different positive threshold voltages (VT+) and negative threshold voltages (VT−). The state flips only when the input signal rises above VT+ or falls below VT−, effectively suppressing small fluctuations and high-frequency noise interference near the threshold.

[0074] After processing by this circuit, the original analog pulses, which suffered from edge distortion and amplitude fluctuations, are reconstructed into rectangular wave signals with steep rising and falling edges and stable high / low levels, achieving signal denoising and logic level standardization. Simultaneously, this design also achieves a reliable transition from the analog to the digital domain, ensuring the output signal has a clear logic high / low state and is fully compatible with the electrical characteristics of the input pulses required by subsequent CMOS-based proportional multiplier circuit chips. Through these dual optimizations—noise suppression and level adaptation—the Schmitt trigger shaper significantly improves the system's anti-interference capability in complex electromagnetic environments and the stability of digital logic circuit operation, providing a solid foundation for subsequent processing of high-precision flow data.

[0075] Reference Figure 5 As one implementation of a scaling circuit, it includes:

[0076] The first BCD proportional multiplier has its clock signal input connected to the output of the waveform shaping circuit, its clock inhibit signal output connected to the clock inhibit signal input and the strobe signal input of the second BCD proportional multiplier, and its pulse original code signal output connected to the cascade signal input of the second BCD proportional multiplier.

[0077] The second BCD proportional multiplier has its clock signal input connected to the output of the waveform shaping circuit.

[0078] The BCD code input terminals of the first and second BCD proportional multipliers are respectively configured as the high and low bits of the preset proportional coefficient.

[0079] The preset proportional coefficient K is determined based on the turbine blade tilt angle 33, the average rotation radius of the turbine, and the cross-sectional area of ​​the flow channel where the turbine is located.

[0080] In this embodiment, the proportional multiplier circuit functions to perform hardware-level proportional conversion on the pulse frequency signal output from the preceding Schmitt trigger circuit according to a preset proportional coefficient K. This eliminates the indication deviation caused by the sensor's instrument coefficient not being 1, thereby obtaining the true pulse frequency output corresponding to the actual oxygen supply flow rate. This circuit is constructed using a BCD proportional multiplier integrated circuit, precisely controlling the number of output pulses by setting the BCD input code, achieving high-precision, real-time digital proportional calculation.

[0081] Specifically, the output terminal U_B of the waveform shaping circuit is connected to the clock signal input terminal CP of the first BCD proportional multiplier IC3 and IC4, serving as a unified input clock source. The strobe signal input terminal ST, clock inhibit signal input terminal INH_IN, cascade signal input terminal CF, reset signal input terminal CR, and set-9 signal input terminal SET "9" of the first BCD proportional multiplier IC3 are all connected to the ground terminal VSS, i.e., in an inactive state; its power input terminal VDD is connected to the operating power supply to ensure normal power supply. The clock inhibit signal output terminal INH_OUT of the first BCD proportional multiplier IC3 is connected to the clock inhibit signal input terminal INH_IN and the strobe signal input terminal ST of the second BCD proportional multiplier IC4, realizing synchronous enable control between the two stages of chips. The pulse original code signal output terminal Q of the first BCD proportional multiplier IC3 is connected to the cascade signal input terminal CF of the second BCD proportional multiplier IC4, used to transmit intermediate calculation results.

[0082] Furthermore, the reset signal input terminal CR and the set-9 signal input terminal SET "9" of the second BCD proportional multiplier IC4 are also connected to the ground terminal VSS to maintain an inactive state; its power input terminal VDD is connected to the operating power supply. Regarding the BCD data input configuration: the B and D terminals of the first BCD proportional multiplier IC3 are connected to the power supply (high level), and the A and C terminals are grounded (low level), corresponding to binary input

[0101] 2, i.e., decimal number A=5; the C and D terminals of the second BCD proportional multiplier IC4 are connected to the power supply, and the A and B terminals are grounded, corresponding to binary input

[0011] 2, i.e., decimal number B=3. Finally, the pulse original code signal output terminal Q of the second BCD proportional multiplier IC4 outputs the proportionally converted pulse signal, denoted as frequency U_C.

[0083] The core purpose of this proportional multiplier circuit is to solve the problem that the instrument coefficient K≠1 caused by the structural parameters of turbine flow sensors, which prevents the original count value from directly representing the actual flow rate. By using a BCD proportional multiplier chip, the input pulse number N_CP can be scaled in real time according to the calibrated K value (e.g., 0.53), and the output pulse number N_0 satisfies the following relationship: ;

[0084] Here, BCD is the decimal value corresponding to the set four-digit binary-decimal code. For example, when the BCD input is 5, only 5 valid pulses are output for every 10 clock pulses input, achieving a frequency division ratio of 1:0.5.

[0085] In this embodiment, a proportional addition module is composed of two BCD proportional multiplier chips, with high-order and low-order proportional coefficients set separately to achieve finer proportional adjustment. The total number of output pulses is determined by the following formula:

[0086] ;

[0087] In the formula, A is the decimal number corresponding to the high-order BCD code, and B is the decimal number corresponding to the low-order BCD code. Substituting the parameters A=5 and B=3 in this example, we get:

[0088] ;

[0089] That is, the number of output pulses is 0.53 times the number of input pulses, thereby achieving a proportional conversion of K=0.53 and obtaining an output signal consistent with the actual flow rate.

[0090] The handling method is similar for other K values. For example, if a proportional conversion is required when K=0.536, it can be achieved by extending to a three-stage proportional multiplier or adjusting the input encoding method to ensure the output pulse count meets the following requirements:

[0091] ;

[0092] Where A is the most significant bit input, B is the second most significant bit input, and C is the least significant bit input. The circuit connection method is the same as in the previous embodiment.

[0093] The proportional multiplication circuit described in this embodiment utilizes a dedicated digital integrated circuit chip to directly perform proportional conversion of pulse signals through hardware logic without the need for a microprocessor. This avoids software delays and calculation errors, ensuring the real-time performance and accuracy of flow data processing. It also possesses good configurability and stability, making it suitable for applications requiring high-reliability measurement of oxygen supply flow in aviation environments.

[0094] Reference Figure 1 As one implementation of the bus conversion unit, it includes:

[0095] The frequency measurement module is used to synchronously count the number of pulses of the calibration pulse signal and the high-stability clock signal within a preset gate time, and calculate the real-time frequency value of the calibration pulse signal based on the pulse count ratio.

[0096] The flow calculation module is used to convert real-time frequency values ​​into instantaneous oxygen supply flow values ​​based on the linear relationship between turbine speed and flow rate.

[0097] The protocol encapsulation module is used to map the instantaneous oxygen supply flow rate value to the 32-bit data segment of the ARINC429 protocol through the custom ARINC429 protocol management soft core integrated inside the FPGA. After adding tag bits, symbol status bits and parity bits, Manchester Type II encoding is performed to obtain the ARINC429 protocol data frame.

[0098] In this embodiment, the bus conversion unit uses a high-performance FPGA as its core to build a highly reliable data acquisition and protocol conversion system. This unit receives a pulse frequency signal representing oxygen supply flow from the signal processing and conversion unit. After precise measurement and intelligent processing, it drives a differential output circuit to convert the signal into a differential signal conforming to the ARINC429 aviation bus standard, achieving seamless integration with the aircraft's avionics system.

[0099] Reference Figure 1 As one implementation of driving a differential output circuit, it includes:

[0100] The protocol driver chip's input terminal is used to receive ARINC429 protocol data frames output by the bus conversion unit and convert them into differential electrical signals with bipolar return-to-zero codes.

[0101] The impedance matching output module is connected to the output terminal of the protocol driver chip and is used to match the output impedance of the differential electrical signal with the load of the avionics bus network before outputting it.

[0102] Specifically, the entire data processing flow is divided into five stages:

[0103] The first stage involves the input and synchronization of the oxygen supply flow rate frequency signal based on FPGA high-speed I / O. The pulse frequency signal is proportional to the instantaneous oxygen flow rate, but due to its small amplitude and potential high-frequency noise, it needs to be reliably input via a dedicated high-speed input pin on the FPGA. Inside the FPGA, the original signal is first shaped using a Schmitt trigger to effectively suppress noise interference. Subsequently, a register chain consisting of two D flip-flops is used to synchronize the asynchronous external pulse signal to the FPGA's internal system clock domain, preventing the propagation of metastability caused by timing mismatches and ensuring the stability and accuracy of subsequent logic operations.

[0104] The second stage is high-precision frequency measurement, which is completed by an adaptive frequency measurement module in conjunction with an external high-stability clock source. The system uses a 100MHz high-precision temperature-compensated crystal oscillator as the time reference; its frequency stability and temperature drift performance directly affect the overall measurement accuracy. The adaptive frequency measurement module employs an equal-precision frequency measurement method, simultaneously counting the number of pulses N_freq of the measured signal and the number of pulses N_clk of the standard clock within a set pre-gate time (e.g., 1 second). When the gate time ends, the values ​​of the two counters are latched, and the actual frequency of the measured signal is calculated according to the formula F_measure = (N_freq / N_clk) × F_clk. This method maintains consistent measurement accuracy across the entire frequency range, overcoming the ±1 pulse quantization error problem present in traditional direct frequency measurement methods, and exhibits significant accuracy advantages, especially in the low-frequency band.

[0105] The third stage is data preprocessing, including smoothing, error removal, and cache management. For multiple flow values ​​obtained from continuous measurements, the system uses a moving average filtering algorithm for smoothing to eliminate the impact of random jitter and output a stable flow data sequence. Simultaneously, a reasonable data change rate threshold is set. If the deviation between the current measurement value and the previous valid value exceeds this threshold, it is determined to be abnormal data or an outlier caused by external interference. The system automatically discards this data and replaces it with the previous valid value, thus ensuring the validity and continuity of the output data. The processed accurate flow values ​​are written into a first-in-first-out (FIFO) memory. This cache module decouples the high-speed measurement process at the front end from the relatively low-speed ARINC429 bus transmission process at the back end, serving as a data buffer and timing match to avoid data loss due to transmission rate mismatch.

[0106] The fourth stage is protocol encapsulation, completed by a custom ARINC429 protocol management soft core integrated within the FPGA. This soft core is the core logic module for implementing bus communication functions, responsible for framing the flow data according to the ARINC429 standard format. Specifically, after reading the flow value from the FIFO, it is assembled into a 32-bit data word: bits 1 to 8 are the Label field, used to uniquely identify the data as "oxygen supply flow" information; bits 9 and 10 are the SDI (Source / Destination Identifier), used to indicate the source or target device of the message; bits 11 to 29 are the data field, where the flow value is encoded in BCD code; bits 30 and 31 are the SSM (Symbol / State Matrix), representing the state information of the data and the sign direction of the physical quantity; bit 32 is the odd parity bit, used to verify the first 31 bits (bits 1 to 31) of data. The soft core also includes a baud rate generator, which can accurately generate a 100kHz transmission clock, strictly controlling the transmission timing of each bit to ensure that the ARINC429 bus's transmission rate requirements are met. In addition, the soft core automatically calculates the parity of the first 31 bits of data and fills the result into the highest bit (32 bits), providing basic single-bit error detection capability.

[0107] The fifth stage is signal encoding and drive output, including parallel-to-serial conversion, Manchester Type II encoding, level conversion, and bus driving. The 32-bit parallel data output from the protocol soft core is sent to the parallel-to-serial converter. Under the control of the baud rate clock, it is output bit by bit starting from the most significant bit (MSB) to form a serial NRZ data stream. Then, Manchester Type II encoding is performed, converting the NRZ code into Manchester code with transitions: a level transition occurs in the middle of each cycle, where a high-to-low transition represents logic "1", and a low-to-high transition represents logic "0". This encoding method has built-in clock information, which is beneficial for the receiver to restore synchronization, and it has zero DC component characteristics, making it suitable for long-distance transmission. Because the Manchester code signal level output by the FPGA core is low (e.g., 1.2V), it cannot directly drive the aviation bus. Therefore, a drive level conversion circuit is needed to convert it into a differential signal conforming to the ARINC429 electrical specification.

[0108] Ultimately, the system employs a dedicated ARINC429 line driver chip, HS-3282, to receive the single-ended TTL signal output from the FPGA and convert it into ±10V differential voltage signals (HI and LO). This chip possesses sufficient driving capability and anti-interference performance, and is directly connected to the aircraft avionics bus network via a rear connector. Thus, the standard ARINC429 differential data stream representing oxygen flow is stably and reliably transmitted to other devices in the avionics system, such as the flight management system and display units, completing the entire measurement and communication process.

[0109] In summary, this application addresses the problems of low measurement accuracy, slow response, susceptibility to interference, and poor reliability of traditional mechanical flow meters in aviation pilot oxygen supply systems under extreme environments such as high speed, high maneuverability, and strong electromagnetic interference. It proposes an oxygen supply flow detection and avionics bus conversion system based on a reflective fiber optic turbine. This system achieves high-precision, real-time monitoring of oxygen supply flow and standardized avionics signal output through a multidisciplinary, integrated "optical-mechanical-electronic" collaborative design.

[0110] The specific implementation principle of this application is as follows: oxygen is shaped into a stable axial airflow by the guide vane 2, which drives the turbine to rotate. The turbine speed and the gas flow velocity have a strict linear relationship, completing the efficient conversion of fluid kinetic energy into mechanical rotational kinetic energy. Subsequently, the optical sensing stage is entered. Non-contact reflective fiber optic technology is used. A high-reflectivity film is attached to the end face of the turbine blade 33. A Y-type fiber optic probe is used to emit a light source and receive periodically reflected light signals. Every time the blade 33 rotates once, a light pulse sequence corresponding to the number of blades 33 is generated. In this way, the rotation speed information is converted into an optical signal without wear and without interference, completely avoiding the wear and electromagnetic sensitivity problems caused by traditional mechanical contact.

[0111] After entering the signal processing stage, the optical pulse signal is converted into a weak current signal by a photodiode, amplified by a transimpedance amplifier and noise filtered out, and then shaped into a standard square wave by a Schmitt trigger to eliminate jitter and glitches. Subsequently, the signal is converted into a hardware-level flow rate by a proportional multiplier circuit according to a preset calibration coefficient K, outputting the actual flow rate pulse. The FPGA uses an equal-precision frequency measurement method to perform high-precision measurement of the pulse frequency, and combines it with algorithms such as buffer smoothing and outlier removal to accurately calculate the instantaneous oxygen supply flow rate. Finally, in the bus output stage, the FPGA integrates an ARINC429 protocol soft core to automatically complete data framing (including tags, data, SSM status bits, and parity check), Manchester Type II encoding, and converts the signal into a bipolar return-to-zero code differential signal conforming to aviation standards through a differential driver chip, which is then stably transmitted to the flight control and avionics system.

[0112] At the signal processing level, this application constructs an FPGA-based adaptive high-precision frequency measurement and real-time data processing architecture. The front-end photoelectric conversion circuit adopts a transimpedance amplification structure, combined with an RC low-pass filter network, to convert the weak photocurrent into a voltage pulse with a moderate amplitude and effectively suppress high-frequency noise. Subsequently, the original waveform is shaped by a Schmitt trigger to remove "glitch" and generate a standard square wave signal, improving anti-interference capability and logic compatibility. The core frequency measurement module implements an equal-precision frequency measurement algorithm based on FPGA, synchronously counting the number of measured pulses and a high-stability clock pulse (provided by an external 100MHz temperature-controlled crystal oscillator) within a preset gate time, fundamentally eliminating ±1 counting error and achieving high-precision frequency measurement across the entire range, especially in the low-frequency band. The measured frequency data is further processed by a moving average filter and an adaptive outlier elimination algorithm to effectively smooth out random fluctuations, identify abnormal jumps, and ensure the continuity, accuracy, and stability of the output data.

[0113] More importantly, this application achieves integrated conversion from pulse frequency to standard avionics bus signals. The system adopts an FPGA-based hardware-level ARINC429 protocol conversion mechanism, integrating an ARINC429 protocol management soft core within the chip. This core automatically completes data framing, tag encoding, parity calculation, and Manchester Type II encoding, and outputs twisted-pair differential signals conforming to ARINC429 electrical specifications via a professional differential driver chip. This design eliminates the need for traditional external protocol conversion modules, requiring no additional MCU or dedicated communication chips. It directly completes the entire process from raw optical pulses to standard avionics signals on a single hardware platform, greatly simplifying the system architecture, reducing power consumption and failure risks, and achieving seamless integration with the aircraft avionics network.

[0114] This application also embodies a highly integrated, cohesive design concept. The fiber optic turbine sensing unit, photoelectric conversion circuit, digital signal processing module, and avionics bus interface function are organically integrated into a single physical unit, forming a compact intelligent sensor that integrates sensing, conditioning, computing, and communication. This integrated structure not only meets the stringent space and weight constraints of airborne equipment but also significantly reduces the number of external connection nodes and connectors, fundamentally lowering the probability of system failures caused by poor contact or aging wiring, and greatly improving overall reliability and maintainability.

[0115] Furthermore, this application possesses excellent scalability for future intelligent oxygen supply systems. The built-in data preprocessing engine supports flow trend analysis, abrupt change detection, and short-term prediction functions, providing a high-quality, low-latency data foundation for the subsequent implementation of closed-loop on-demand oxygen supply (SMODS) based on pilot physiological status. Simultaneously, thanks to the programmability of the FPGA, the system protocol layer is highly flexible and can be quickly adapted to other mainstream avionics bus standards, such as MIL-STD-1553B and ARINC664, through software reconfiguration to meet the development needs of next-generation integrated avionics systems.

[0116] This application also discloses a method for detecting oxygen supply flow rate and avionics conversion using a reflective fiber optic turbine.

[0117] Reference Figure 6 A method for detecting and converting oxygen supply flow rate of a reflective fiber optic turbine into avionics components, applied to the aforementioned reflective fiber optic turbine oxygen supply flow rate detection and avionics conversion system; the method includes:

[0118] Step S101: The oxygen supply flow to be tested is rectified and then sent to the turbine to drive the turbine to rotate, and the periodic light pulse signal generated by the turbine rotation is collected.

[0119] Step S102: The periodic optical pulse signal is converted into a voltage pulse signal and processed in stages. After waveform shaping and scaling, a calibration pulse signal is obtained.

[0120] Step S103: Measure the frequency of the calibration pulse signal, calculate the instantaneous oxygen supply flow rate, and convert the instantaneous oxygen supply flow rate into an ARINC429 protocol data frame;

[0121] Step S104: Convert the ARINC429 protocol data frame into a bipolar return-to-zero code differential electrical signal and output it to the avionics bus network.

[0122] Reference Figure 7 As one implementation of step S103, the step of converting the instantaneous oxygen supply flow rate value into an ARINC429 protocol data frame includes:

[0123] Step S201: Map the instantaneous oxygen supply flow rate value to a 32-bit data segment of the ARINC429 protocol;

[0124] Step S202: Add tag bit, sign status bit, and parity check bit;

[0125] Step S203: Perform Manchester Type II encoding on the 32-bit data segment to obtain the ARINC429 protocol data frame.

[0126] The reflective fiber optic turbine oxygen supply flow detection and avionics conversion system of this application embodiment can implement any of the above methods, and the specific working process of each module in the system can refer to the corresponding process in the above method embodiment.

[0127] The airborne oxygen supply flow detection and avionics bus conversion system based on reflective fiber optic turbines provided in this application represents a fundamental leap from traditional mechanical sensing to a non-contact optical sensing and intelligent integrated system. Its innovation is concentrated in three aspects: at the principle level, it breaks through the physical limitations of traditional measurement methods; at the architectural level, it completes the functional upgrade from an independent sensor to an intelligent node in the avionics network; and at the application prospect level, it lays a solid foundation for the development of future intelligent aviation life support systems.

[0128] First, in terms of fundamental innovation, this invention fundamentally solves the inherent performance bottlenecks of traditional mechanical or electromagnetic flow detection technologies. Existing technologies rely on impeller rotation driving magnetic coupling elements or Hall effect devices for signal acquisition, inevitably suffering from response lag due to mechanical inertia, decreased reliability due to wear of moving parts, and data distortion caused by susceptibility to interference in the electromagnetic induction path. This invention creatively introduces a non-contact optical sensing mechanism called a "reflective fiber optic turbine." By attaching a high-reflectivity film to the turbine blade end face and combining it with a Y-shaped branched fiber optic probe to form a reflective optical path structure, it achieves pure optical detection of turbine rotation speed. This design completely eliminates the electrical signal coupling link in traditional schemes, completely separating the measurement process from the electromagnetically sensitive path, thus giving the system natural anti-interference capabilities in complex airborne electromagnetic environments. Simultaneously, since optical detection requires no physical contact, it eliminates mechanical friction and transmission inertia, significantly improving dynamic response speed and enabling real-time capture of instantaneous changes in oxygen flow rate. Furthermore, in conjunction with an FPGA-based adaptive equal-precision frequency measurement algorithm, the measured pulse and the standard clock pulse are counted synchronously with the support of a highly stable clock source, effectively eliminating ±1 counting errors and achieving high-precision frequency measurement across the entire range, especially in the low-frequency band. These fundamental innovations have resulted in substantial improvements in measurement accuracy, response speed, and operational stability, truly achieving the goal of high reliability, high interference immunity, and high real-time performance in flight oxygen supply monitoring.

[0129] Secondly, in terms of architectural innovation, this application achieves a key leap from a single-function sensor to a highly integrated avionics system node. Unlike traditional flowmeters that only output analog or non-standard digital signals and rely on external modules for protocol conversion, this solution adopts a multidisciplinary collaborative design concept of "optics-mechanical-electronics," organically integrating fiber optic sensing units, photoelectric conversion circuits, signal conditioning modules, digital processing engines, and avionics bus interfaces into a single physical unit, forming a compact intelligent sensor that integrates sensing, processing, and communication. This integrated architecture significantly reduces the number of external connection cables, connectors, and intermediate conversion devices, significantly reducing the risk of failures caused by poor contact, aging lines, or module failures at the system level, improving the overall system reliability and maintainability, while meeting the stringent requirements of aviation equipment for lightweighting and miniaturization. Crucially, this invention innovatively employs FPGA-based hardware-level protocol packaging technology, building an ARINC429 protocol soft core within the chip to directly complete flow data framing encoding, parity calculation, Manchester Type II encoding, and differential drive output, replacing the traditional external protocol chip or multi-level MCU processing flow. This design achieves full-process on-chip processing from the original pulse frequency to the standard ARINC429 differential signal, with seamless "plug and play" access capability. It completely solves the problems of transmission delay, poor compatibility and high system complexity caused by multi-level signal conversion in traditional solutions, and completes the functional leap from "sensor" to "avionics network functional node".

[0130] Finally, in terms of forward-looking innovation, this invention demonstrates strong scalability and support for the development of future intelligent aviation equipment. The system's built-in data preprocessing engine possesses edge computing functions such as real-time moving average filtering, outlier removal, and trend prediction. It not only outputs stable and reliable instantaneous flow data but also provides intelligently optimized trend information, providing a high-quality data foundation and controllable interface for subsequent implementation of closed-loop on-demand oxygen supply control (SMODS) based on pilot physiological status. Furthermore, thanks to the programmable nature of the FPGA platform, the system's communication protocol layer is highly flexible. It can be quickly adapted to next-generation avionics bus standards such as MIL-STD-1553B and ARINC664 through software reconfiguration, meeting the avionics integration needs of different aircraft models or upgraded versions without hardware modifications. This flexible architecture design endows the product with continuous evolution capabilities throughout its entire lifecycle, enabling it not only to serve current mainstream aviation platforms but also to be embedded as a core component in next-generation integrated and intelligent avionics systems.

[0131] In summary, this application, through a fundamental non-contact optical sensing innovation, fundamentally overcomes the inherent deficiencies of traditional mechanical and electromagnetic sensing technologies in terms of accuracy, response, and interference immunity. Through an architecturally innovative optoelectronic-bus integration, it achieves a functional leap from isolated measuring devices to standardized avionics functional nodes. Furthermore, its forward-looking programmable and intelligent features provide key technical support for the autonomous adjustment and intelligent decision-making of future aviation life support systems. This solution not only significantly improves the safety and reliability of pilot oxygen supply systems but also opens up a practical technical path for the development of modern aircraft towards intelligence and integration.

[0132] In the several embodiments provided in this application, it should be understood that the provided methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for example, the division of a certain module is merely a logical functional division, and in actual implementation there may be other division methods, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed.

[0133] In this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0134] Although this application has been described herein in conjunction with various embodiments, those skilled in the art, by reviewing the accompanying drawings, disclosure, and appended claims, will understand and implement other variations of the disclosed embodiments in carrying out the claimed application. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude a plurality. A single processor or other unit can implement several functions listed in the claims. While different dependent claims may recite certain measures, this does not mean that these measures cannot be combined to produce a good effect.

[0135] The above are all preferred embodiments of this application and are not intended to limit the scope of protection of this application. Any feature disclosed in this specification (including the abstract and drawings) may be replaced by other equivalent or similar features unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is only one example of a series of equivalent or similar features.

Claims

1. A reflective fiber optic turbine oxygen supply flow detection and avionics conversion system, characterized in that, The system includes: The fiber optic turbine oxygen supply flow detection unit is used to rectify the oxygen supply flow to be detected and then send it to the turbine to drive the turbine to rotate, and to collect the periodic optical pulse signal generated by the rotation of the turbine. The signal processing and conversion unit is used to convert the periodic optical pulse signal into a voltage pulse signal and perform hierarchical processing. After waveform shaping and scaling, a calibration pulse signal is obtained. The bus conversion unit measures the frequency of the calibration pulse signal, calculates the instantaneous oxygen supply flow rate, and converts the instantaneous oxygen supply flow rate into an ARINC429 protocol data frame. After reading the flow rate value from the FIFO, the flow rate value is assembled into a 32-bit data word: bits 1 to 8 are the Label field, used to uniquely identify the data as oxygen supply flow rate information; bits 9 and 10 are the SDI, used to indicate the message source or target device; bits 11 to 29 are the data field, where the flow rate value is encoded in BCD code; bits 30 and 31 are the SSM, representing the data's status information and the sign direction of the physical quantity; and bit 32 is the odd parity bit, used to verify the first 31 bits of data. The differential output circuit is used to convert the ARINC429 protocol data frame into a bipolar return-to-zero code differential electrical signal and output it to the avionics bus network.

2. The reflective fiber optic turbine oxygen supply flow detection and avionics conversion system according to claim 1, characterized in that, The fiber optic turbine oxygen supply flow detection unit includes a housing, a flow guide, a turbine assembly, and a reflective fiber optic sensor. The flow guide is fixedly installed inside the oxygen inlet of the shell and is used to rectify the oxygen supply flow to be tested into an axial airflow. The turbine assembly includes a rotating shaft rotatably disposed within the housing and blades covered with reflective sheets. The rotating shaft is coaxially fixed to the guide vane via bearings, and the blades are fixedly disposed on the rotating shaft. The blades are used to rotate under the push of axial airflow. The reflective fiber optic sensor includes a Y-shaped fiber optic assembly, a light source, and an optical lens; wherein, the optical lens is disposed at the end of the Y-shaped fiber optic assembly for collimating the emitted light beam and focusing the reflected light signal; the emitting branch of the Y-shaped fiber optic assembly is used to emit a light beam from the light source onto the blade, and the receiving branch is used to capture the light pulse signal periodically reflected by the reflector of the blade.

3. The reflective fiber optic turbine oxygen supply flow detection and avionics conversion system according to claim 1, characterized in that, The signal processing and conversion unit includes a photoelectric conversion circuit, a waveform shaping circuit, and a scaling circuit. The photoelectric conversion circuit includes a photodiode and an operational amplifier; wherein, the photodiode converts the periodic light pulse signal into a current signal; the operational amplifier amplifies and filters the current signal into a voltage pulse signal through a transimpedance amplifier circuit composed of a feedback resistor and a parallel capacitor; The waveform shaping circuit is used to receive the voltage pulse signal, eliminate signal jitter by comparing hysteresis voltage, and output a standard square wave signal. The scaling circuit is used to receive a standard square wave signal and a binary encoded value of a preset scaling factor, and output a calibration pulse signal after scaling the number of pulses proportionally.

4. The reflective fiber optic turbine oxygen supply flow detection and avionics conversion system according to claim 3, characterized in that, The waveform shaping circuit includes: The fifth capacitor has one end connected to the output terminal of the photoelectric conversion circuit; A Schmitt trigger consists of two inverter stages; the input of the first inverter is connected to the other end of the fifth capacitor, the output of the first inverter is connected to the input of the second inverter, and the output of the second inverter is used to generate a standard square wave signal.

5. The reflective fiber optic turbine oxygen supply flow detection and avionics conversion system according to claim 3, characterized in that, The scaling circuit includes: The first BCD proportional multiplier has its clock signal input connected to the output of the waveform shaping circuit, its clock inhibit signal output connected to the clock inhibit signal input and the strobe signal input of the second BCD proportional multiplier, and its pulse original code signal output connected to the cascade signal input of the second BCD proportional multiplier. The second BCD proportional multiplier has its clock signal input connected to the output of the waveform shaping circuit. The BCD code input terminals of the first and second BCD proportional multipliers are respectively configured as the high and low bits of the preset proportional coefficient.

6. The reflective fiber optic turbine oxygen supply flow detection and avionics conversion system according to claim 3, characterized in that, The preset proportional coefficient is determined based on the turbine blade inclination angle, the average rotation radius of the turbine, and the cross-sectional area of ​​the flow channel where the turbine is located.

7. The reflective fiber optic turbine oxygen supply flow detection and avionics conversion system according to claim 1, characterized in that, The bus conversion unit includes: The frequency measurement module is used to synchronously count the number of pulses of the calibration pulse signal and the high-stability clock signal within a preset gate time, and calculate the real-time frequency value of the calibration pulse signal based on the pulse count ratio. The flow calculation module is used to convert the real-time frequency value into an instantaneous oxygen supply flow value based on the linear relationship between turbine speed and flow rate. The protocol encapsulation module is used to map the instantaneous oxygen supply flow rate value to a 32-bit data segment of the ARINC429 protocol through the custom ARINC429 protocol management soft core integrated inside the FPGA. After adding tag bits, symbol status bits and parity bits, Manchester Type II encoding is performed to obtain the ARINC429 protocol data frame.

8. The reflective fiber optic turbine oxygen supply flow detection and avionics conversion system according to claim 1, characterized in that, The driving differential output circuit includes: The protocol driver chip's input terminal is used to receive ARINC429 protocol data frames output by the bus conversion unit and convert them into differential electrical signals with bipolar return-to-zero codes. An impedance matching output module is connected to the output terminal of the protocol driver chip and is used to match the output impedance of the differential electrical signal with the load of the avionics bus network before outputting it.

9. A method for detecting oxygen supply flow rate and converting avionics using a reflective fiber optic turbine, characterized in that, The method is applied to a reflective fiber optic turbine oxygen supply flow detection and avionics conversion system according to any one of claims 1 to 8; the method includes: The oxygen supply flow to be tested is rectified and then sent to the turbine to drive the turbine to rotate, and the periodic light pulse signal generated by the turbine rotation is collected. The periodic optical pulse signal is converted into a voltage pulse signal and processed in stages. After waveform shaping and scaling, a calibration pulse signal is obtained. The frequency of the calibration pulse signal is measured, the instantaneous oxygen supply flow rate is calculated, and the instantaneous oxygen supply flow rate is converted into an ARINC429 protocol data frame. The ARINC429 protocol data frame is converted into a bipolar return-to-zero code differential electrical signal and output to the avionics bus network.

10. The method for detecting oxygen supply flow rate and converting avionics using a reflective fiber optic turbine according to claim 9, characterized in that, The steps for converting the instantaneous oxygen supply flow rate value into an ARINC429 protocol data frame include: Map the instantaneous oxygen supply flow rate value to a 32-bit data segment of the ARINC429 protocol; Add a tag bit, a sign status bit, and a parity bit; Manchester Type II encoding is performed on the 32-bit data segment to obtain an ARINC429 protocol data frame.

Images