Emergency judgment method and system for unmanned helicopter rotor rotating speed sensor failure

Abstract

The present application relates to a kind of unmanned helicopter rotor speed sensor failure emergency determination method and system, belong to unmanned helicopter flight control and health management technical field, solve the problem that rotor speed sensor fails and cannot reliably obtain rotor speed.The first data including three-axis body vibration acceleration or including three-axis body vibration acceleration, engine parameter, transmission system operating parameter and rotor related vibration data collected by vibration sensor are collected when rotor speed sensor output signal fails;Frequency and amplitude are obtained according to the first data;Rotor speed is obtained based on frequency;Whether the rotor speed needs to be corrected based on amplitude and the first data or based on amplitude is judged, if needed, the rotor speed is corrected according to amplitude.The present application breaks through the single dependence of traditional engine speed conversion, realizes reliable estimation and fault diagnosis of rotor speed under different hardware configurations by multiplexing fuselage vibration data and vibration sensor data.

Description

Technical Field

[0001] This invention relates to the field of flight control and health management technology for unmanned helicopters, and in particular to an emergency judgment method and system for rotor speed sensor failure in unmanned helicopters. Background Technology

[0002] With its advantages such as vertical take-off and landing and stable hovering, unmanned helicopters are widely used in many fields such as emergency rescue, power line inspection, environmental monitoring, and material delivery. Rotor speed is the core parameter of unmanned helicopter flight control, which directly affects flight attitude stability and lift control accuracy, and the reliability of its data collection is of paramount importance.

[0003] Currently, unmanned helicopters primarily acquire rotor speed signals directly through rotor speed sensors. However, their operating environment is complex and susceptible to electromagnetic interference, mechanical vibration, and environmental dust, leading to sensor failure (such as signal interruption or distortion). Existing technology typically compensates for the missing rotor speed signal by converting engine speed to rotor speed based on the transmission ratio when the rotor speed sensor fails. However, this method has significant drawbacks: the transmission system (such as belts, gears, and drive shafts) may experience slippage, wear, or breakage, causing changes in the transmission ratio between engine and rotor speeds. In this case, the calculated rotor speed deviates significantly from the actual rotor speed, or is even completely distorted, failing to meet the accuracy requirements of flight control and easily leading to flight loss of control.

[0004] Furthermore, modern unmanned helicopters are all equipped with inertial measurement units (IMUs) for flight attitude control. For medium-to-large or industrial-grade unmanned helicopters, vibration sensors are usually added to monitor the health status of moving parts to further ensure flight safety. However, whether relying solely on the IMU or combining it with vibration sensors, current technologies have failed to effectively utilize this airborne data to solve the problem of emergency rotor speed acquisition after rotor speed sensor failure. There has long been a technological bias in this field that fuselage vibration data contains a large amount of attitude motion, aerodynamic noise, and structural modal interference, making it difficult to extract pure rotor speed characteristics from it. This results in the aforementioned high-value airborne data being idle in emergency situations, forcing emergency solutions to be limited to passive calculation of engine speed.

[0005] In summary, there is an urgent need for an emergency judgment method that can eliminate dependence on the drivetrain after the rotor speed sensor fails, and can simultaneously diagnose transmission system faults. Summary of the Invention

[0006] Based on the above analysis, the present invention aims to provide an emergency judgment method and system for rotor speed sensor failure of unmanned helicopters, so as to solve the problem that rotor speed cannot be reliably obtained after rotor speed sensor failure in the prior art.

[0007] On one hand, embodiments of the present invention provide an emergency determination method for the failure of a rotor speed sensor in an unmanned helicopter, comprising the following steps: Monitor the output signal of the rotor speed sensor; The rotor speed sensor output signal is used to determine whether the rotor speed sensor is malfunctioning. If it is determined to be malfunctioning, the first data is collected. The frequency and amplitude are calculated based on the first data; The rotor speed is calculated based on the frequency. When the first data only includes the triaxial body vibration acceleration, it is determined whether the rotor speed needs to be corrected based on the amplitude; when the first data includes the triaxial body vibration acceleration, engine parameters, transmission system operating parameters, and rotor-related vibration data collected by vibration sensors, it is determined whether the rotor speed needs to be corrected based on the amplitude and the first data; if it is determined that correction is needed, the rotor speed is corrected according to the amplitude.

[0008] In some embodiments, determining whether the rotor speed sensor is malfunctioning based on the output signal of the rotor speed sensor includes: If the interruption time of the rotor speed sensor output signal exceeds a preset time threshold, or if the fluctuation of the rotor speed sensor output signal exceeds a fluctuation threshold and the duration exceeds a preset time threshold, then the rotor speed sensor is determined to be faulty.

[0009] In some embodiments, when the first data only includes triaxial body vibration acceleration, calculating the frequency and amplitude based on the first data includes: Select the Z-axis body vibration acceleration from the three-axis body vibration acceleration; The Z-axis machine body vibration acceleration is low-pass filtered; Frequency domain analysis was performed on the filtered Z-axis body vibration acceleration to obtain the frequency and amplitude.

[0010] In some embodiments, determining whether the rotor speed needs to be corrected based on the amplitude, and correcting the rotor speed based on the amplitude when the determination is made as needed, includes: Determine whether the amplitude is within the amplitude threshold range. If it is within the amplitude threshold range, the rotor speed is confirmed to be valid. If it is not within the amplitude threshold range, the rotor speed is confirmed to be abnormal. Determine the correction coefficient based on the amplitude, and multiply the rotor speed by the correction coefficient to obtain the corrected rotor speed.

[0011] In some embodiments, it also includes: Collect engine speed; The converted speed is obtained by converting the engine speed according to the nominal transmission ratio. Determine whether the absolute or relative deviation between the rotor speed and the calculated speed is greater than a preset deviation value. If so, output a warning message indicating a possible abnormality in the transmission system.

[0012] In some embodiments, it also includes: Based on different situations where the amplitude exceeds the preset amplitude threshold range, graded early warnings are issued and graded early warning signals are output.

[0013] In some embodiments, the rotor-related vibration data includes a first frequency and a first amplitude. When the first data includes triaxial airframe vibration acceleration, engine parameters, transmission system operating parameters, and rotor-related vibration data collected by vibration sensors, the frequency and amplitude are calculated based on the first data, including: Select the Z-axis body vibration acceleration from the three-axis body vibration acceleration; The Z-axis machine body vibration acceleration is low-pass filtered; Frequency domain analysis was performed on the filtered Z-axis body vibration acceleration to obtain the second frequency and the second amplitude. A fusion frequency is obtained by fusing the first frequency and the second frequency, and a fusion amplitude is obtained by fusing the first amplitude and the second amplitude.

[0014] In some embodiments, determining whether the rotor speed needs to be corrected based on the amplitude and the first data, and if so, correcting the rotor speed according to the amplitude, including: Verify the amplitude: determine whether the amplitude is within the amplitude threshold range; Verify the engine speed, including the engine parameters: determine whether the absolute or relative deviation between the rotor speed and the converted speed of the engine is less than a preset deviation value; Verify the operating parameters: determine whether the transmission system operating parameters and the engine parameters, including the engine throttle opening or torque command, meet the preset requirements; If only the amplitude verification fails, the rotor speed is corrected.

[0015] In some embodiments, correcting the rotor speed includes: The equivalent rotational speed is obtained by converting the engine speed to the nominal transmission ratio. The deviation rate and deviation direction are determined based on the rotor speed and the equivalent rotational speed. The rotor speed is then corrected based on the deviation rate and deviation direction.

[0016] On the other hand, embodiments of the present invention provide an emergency judgment system for the failure of a rotor speed sensor of an unmanned helicopter, including: Rotor speed sensor failure monitoring module: Used to monitor the output signal of the rotor speed sensor and determine whether the rotor speed sensor has failed based on the output signal of the rotor speed sensor; Data acquisition module: Used to acquire the first data if the judgment fails; Data processing and fusion module: used to calculate the frequency and amplitude based on the first data; Rotor speed estimation and verification module: used to calculate the rotor speed based on the frequency; when the first data only includes the triaxial body vibration acceleration, it determines whether the rotor speed needs to be corrected based on the amplitude; when the first data includes the triaxial body vibration acceleration, engine parameters, transmission system operating parameters and rotor-related vibration data collected by vibration sensors, it determines whether the rotor speed needs to be corrected based on the amplitude and the first data; if it is determined that correction is needed, the rotor speed is corrected according to the amplitude.

[0017] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects: 1. Pioneering Application: Breaking through technical biases, it is the first to propose and realize the use of fuselage vibration data for emergency speed estimation after rotor speed sensor failure. The characteristic vibration frequency of the rotor is extracted through a specific signal processing link, fundamentally eliminating the single dependence on the transmission chain.

[0018] 2. Flexible Architecture: A two-tiered flexible technical architecture is proposed, consisting of "fuselage vibration data" and "fuselage vibration data + vibration sensor fusion estimation". The former enables zero-hardware-cost emergency response capabilities "from scratch"; the latter, through weighted fusion algorithms (such as high weighting of vibration sensors) and refined frequency domain analysis, achieves high-precision estimation "from existing to optimal", perfectly adapting to different aircraft models from light to heavy.

[0019] 3. Functional Reuse and Synergy: The vibration sensor achieves dual functionality and synergy with the triaxial body vibration acceleration acquisition equipment. Normally, the vibration sensor independently monitors the health of moving parts; in emergencies, it integrates with data collected by the triaxial body vibration acceleration acquisition equipment to form a highly reliable speed estimation source, significantly improving the utilization rate of airborne equipment.

[0020] 4. Intelligent Verification and Diagnosis: A multi-factor verification and correction mechanism based on vibration amplitude threshold, cross-verification of engine converted speed, and auxiliary judgment of transmission system parameters has been constructed. This mechanism can not only output high-precision emergency speed, but also simultaneously diagnose faults such as rotor imbalance and transmission system slippage / wear, and realize safety early warning.

[0021] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0022] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0023] Figure 1 This is a flowchart of the emergency judgment method for rotor speed sensor failure of an unmanned helicopter in Embodiment 1 of the present invention; Figure 2 This is a flowchart of the emergency judgment method for scenarios where vibration sensors are not installed in Embodiment 1 of the present invention. Figure 3 This is a flowchart of the emergency judgment method for a scenario where a vibration sensor is installed in Embodiment 1 of the present invention; Figure 4 This is a block diagram of the emergency judgment system architecture for the rotor speed sensor failure of an unmanned helicopter in Embodiment 2 of the present invention. Detailed Implementation

[0024] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0025] In the field of flight control, the real-time performance, stability, and accuracy of feedback signals are extremely critical. Therefore, those skilled in the art have long held the preconceived notion that rotational speed must be obtained using dedicated, direct sensors (such as rotor speed sensors) or deterministic physical transmission relationships (engine speed conversion). Existing unmanned helicopters are equipped with inertial measurement units (IMUs), primarily used to collect fuselage attitude (roll, pitch, yaw) and acceleration data. This data, typically used in core control loops, is considered "unreliable" and "impractical," and has not been used to provide emergency support in case of rotor speed sensor failure. This invention breaks this convention, creatively extracting crucial information from "unavailable" data to provide emergency support in case of rotor speed sensor failure.

[0026] Example 1, A specific embodiment of the present invention discloses an emergency judgment method for the failure of a rotor speed sensor in an unmanned helicopter. This method is applied to a flight control system, such as... Figure 1 As shown, it includes the following steps: S11: Monitor the output signal of the rotor speed sensor.

[0027] S12: Determine whether the rotor speed sensor is malfunctioning based on the output signal of the rotor speed sensor. If it is determined to be malfunctioning, collect the first data.

[0028] S13: Calculate the frequency and amplitude based on the first data.

[0029] S14: Calculate the rotor speed based on the frequency; S15: When the first data only includes the triaxial body vibration acceleration, determine whether the rotor speed needs to be corrected based on the amplitude; when the first data includes the triaxial body vibration acceleration, engine parameters, transmission system operating parameters, and rotor-related vibration data collected by vibration sensors, determine whether the rotor speed needs to be corrected based on the amplitude and the first data; if it is determined that it needs to be corrected, then the rotor speed is corrected according to the amplitude.

[0030] The following description is based on two different implementation examples, each with a different set of first data.

[0031] First embodiment: Emergency estimation without vibration sensors (pure inertial measurement unit (IMU)) This method is suitable for small unmanned helicopters without vibration sensors. Emergency rotation speed estimation can be achieved directly using data collected by the existing onboard IMU (or Attitude and Heading Reference System, AHRS). The steps are as follows: Figure 2 As shown, it includes: Step 1. Failure Determination: In some embodiments, determining whether the rotor speed sensor has failed based on the output signal of the rotor speed sensor (S12) includes: If the interruption time of the rotor speed sensor output signal exceeds a preset time threshold, or if the fluctuation of the rotor speed sensor output signal exceeds a fluctuation threshold and the duration exceeds a preset time threshold, then the rotor speed sensor is determined to be faulty.

[0032] Specifically, the normal signal range of the rotor speed sensor is preset (speed fluctuation threshold ±6%), and the output signal of the rotor speed sensor is monitored in real time. If the signal is interrupted for more than 100ms or the fluctuation exceeds the threshold for more than 100ms, the rotor speed sensor is determined to be faulty.

[0033] Normal signal range: For example, the rated rotor speed of TD550 is 580 rpm, and the normal range is 562.5 rpm to 597.5 rpm. If it exceeds this range, the rotor speed will be considered abnormal.

[0034] A speed fluctuation exceeding the threshold ±3% indicates a warning; a speed fluctuation exceeding the threshold ±6% indicates a fault. Warning speeds are 545 rpm - 562.5 rpm and 597.5 rpm - 615 rpm, while fault speeds are <545 rpm or >615 rpm.

[0035] Step 2. Data Acquisition: Airborne IMUs are used to acquire fuselage vibration acceleration along the x, y, and z axes at a frequency of ≥100Hz. The airborne IMU can be replaced with an Attitude and Bearing Reference System (AHRS), which integrates accelerometers, gyroscopes, and magnetometers, further reducing interference from fuselage attitude changes on vibration data.

[0036] Step 3. Data Processing: In some embodiments, when the first data only includes triaxial body vibration acceleration, the frequency and amplitude are calculated based on the first data, including: Select the Z-axis body vibration acceleration from the three-axis body vibration acceleration; The Z-axis machine body vibration acceleration is low-pass filtered; Frequency domain analysis was performed on the filtered Z-axis body vibration acceleration to obtain the frequency and amplitude.

[0037] Specifically, the triaxial fuselage vibration acceleration data acquired by the IMU were first analyzed. Since the vibration generated by rotor rotation is most significant in the axis perpendicular to the rotor disk plane (usually the fuselage Z-axis), data from this axis was selected for processing first. A low-pass filtering algorithm (cutoff frequency 100Hz) was used to remove high-frequency noise and engine main frequency interference. Subsequently, a radix-2 FFT algorithm was used to perform frequency domain analysis on the filtered signal. In the spectrum, the rotor vibration characteristics exhibited a prominent fundamental frequency peak and its harmonics. The frequency f (unit: Hz) corresponding to this fundamental frequency peak was identified, and its amplitude A was calculated.

[0038] In data processing, the low-pass filtering algorithm can be replaced by the Kalman filtering algorithm, which is suitable for flight scenarios with more complex vibration interference and improves the accuracy of effective signal extraction. In some embodiments, frequency domain analysis can also employ the zoom fast Fourier transform (ZOOM-FFT) algorithm to perform local spectrum refinement analysis in the possible frequency bands of rotor speed, thereby improving frequency extraction accuracy.

[0039] Step 4. Speed ​​estimation and verification: The rotation of the rotor of an unmanned helicopter will generate periodic vibrations. The vibration frequency f (Hz) has a fixed physical relationship with the rotor speed N (r / min): N = f × 60 ÷ number of blades. The rotor speed can be directly calculated by extracting the rotor vibration frequency f, which is not affected by the state of the transmission system.

[0040] In some embodiments, determining whether the rotor speed needs to be corrected based on the amplitude, and correcting the rotor speed based on the amplitude when the determination is made as needed, includes: Determine whether the amplitude is within the amplitude threshold range. If it is within the amplitude threshold range, the rotor speed is confirmed to be valid. If it is not within the amplitude threshold range, the rotor speed is confirmed to be abnormal. Determine the correction coefficient based on the amplitude, and multiply the rotor speed by the correction coefficient to obtain the corrected rotor speed.

[0041] Specifically, if A is within the amplitude threshold range, the rotor speed N is confirmed to be valid; if A exceeds the amplitude threshold range, an anomaly is identified, and the rotor speed N is corrected. A correction coefficient k (range 0.95-1.05) is dynamically generated based on the percentage by which amplitude A exceeds the amplitude threshold using linear or lookup table mapping. Then, the rotor speed is dynamically corrected with a small amplitude based on N_corrected = N × k to address vibration changes caused by slight rotor imbalance or environmental disturbances.

[0042] When the vibration is too large, the value of A is slightly larger. If this exceeds the maximum threshold value, the speed correction should be adjusted to be less than 1, and the speed value should be slightly reduced to reduce the vibration of the machine. Conversely, if the value of A is less than the minimum threshold value, the correction coefficient will be adjusted to be greater than 1, and the speed will be slightly increased to restore the vibration of the machine to normal.

[0043] Among them, the amplitude threshold range is the preset amplitude threshold range under different flight conditions. The safe operation amplitude boundary is obtained by conducting a large number of flight tests on this type of unmanned helicopter under different standard flight conditions (such as hovering, forward flight, and climb), statistically analyzing the distribution of rotor vibration fundamental frequency amplitude data collected by IMU, or by simulation calculation based on rotor aerodynamic model and fuselage structure vibration model.

[0044] The correction coefficient k has a correction range of 0.95-1.05. It is determined based on the simulation analysis and experimental data statistics of the vibration fundamental frequency offset under various typical rotor failure modes (such as blade icing, minor damage, and loose counterweights). It aims to cover the estimation error compensation needs under most non-catastrophic failures.

[0045] In addition, it also includes: Collect engine speed; The converted speed is obtained by converting the engine speed according to the nominal transmission ratio. Determine whether the absolute or relative deviation between the rotor speed and the calculated speed is greater than a preset deviation value. If so, output a warning message indicating a possible abnormality in the transmission system.

[0046] Specifically, engine speed data can also be collected in step 2, data acquisition. Then, the estimated speed N (effective / corrected speed N) is compared with the speed N_engine calculated based on the engine speed according to the nominal transmission ratio. If the relative deviation between the two (|N - N_engine| / N) is consistently greater than a preset value (such as 6%, or other values, set based on actual conditions), a prompt message "Transmission system may be abnormal" will be output.

[0047] 5. Signal output and switching: In some embodiments, it further includes: Based on different situations where the amplitude exceeds the preset amplitude threshold range, graded early warnings are issued and graded early warning signals are output.

[0048] Specifically, the flight control system will replace the failed rotor speed sensor signal with the valid / corrected rotational speed N to perform corresponding flight control.

[0049] Then, the amplitude A is determined. If the amplitude remains abnormal, a graded warning signal is output. The graded warning signal is used to warn of abnormalities in the transmission / rotor system. 1) If the amplitude A is within the threshold range, it is considered normal and there is no warning. Tiered early warning: 2) If the amplitude A exceeds the threshold range and recovers within the first preset time, the rotor will be slightly unbalanced, the transmission system will experience slight wear / slight slippage, and an output warning will be issued. The flight control system will maintain emergency mode and will not restrict flight. 3) If the amplitude A exceeds the threshold range for more than the first preset time, the rotor imbalance will worsen, the transmission slippage will be obvious, and there will be a risk of speed distortion. A warning level warning will be output, and it is recommended to hover and check nearby and simplify the task. 4) If the duration of amplitude A exceeding the threshold exceeds the second preset time (the second preset time is greater than the first preset time), the rotor will be severely unbalanced, the transmission will be close to failure, and flight safety will be endangered. A fault-level alarm will be output, and it is recommended to return to base or land safely at the nearest airport.

[0050] The first preset time and the second preset time are determined based on specific circumstances.

[0051] In the prior art, some unmanned helicopters are equipped with vibration sensors to monitor the vibration status of key parts of the fuselage and to determine the working health of moving parts (such as rotors, gears, and bearings). However, such vibration sensors are only used for fault diagnosis and have not been used for emergency speed estimation after rotor speed sensor failure. This invention uses the data collected by the vibration sensor for emergency speed estimation after rotor speed sensor failure.

[0052] Second embodiment: with vibration sensor (IMU + vibration sensor fusion estimation) Suitable for medium and large unmanned helicopters, the vibration sensor is installed in the output bearing housing of the main gearbox (direct rotor vibration transmission with minimal interference) to achieve high-precision emergency speed estimation, while also taking into account the health monitoring of moving parts. The vibration sensor can be replaced with a piezoelectric vibration sensor or a fiber optic vibration sensor depending on the installation space and data acquisition requirements. The fiber optic sensor is suitable for flight environments with strong electromagnetic interference.

[0053] The steps are as follows Figure 3 As shown, it includes: Step 1. Failure Determination: Same as Step 1 in the first embodiment, and will not be repeated here. Under normal conditions, the vibration sensor is used to monitor the health of moving parts such as the rotor and transmission. If the rotor speed sensor fails, the vibration sensor will be switched to emergency working mode. The vibration sensor maintains its original acquisition frequency and hardware parameters. The vibration data is no longer only used for health monitoring, but also participates in high-frequency domain analysis and speed calculation. The IMU + vibration sensor fusion algorithm is enabled, and the IMU is no longer used alone for estimation.

[0054] Step 2. Dual Data Acquisition: The airborne IMU acquires fuselage vibration acceleration along the x, y, and z axes at a frequency ≥100Hz. Vibration data related to the rotor at the main gearbox is acquired via vibration sensors at a frequency ≥200Hz (first frequency f1, second amplitude A1). Engine parameters and transmission system operating parameters are also acquired simultaneously.

[0055] The engine parameters include engine speed and engine throttle opening / torque command. The transmission system operating parameters include gear meshing frequency, belt tension / slip ratio, main reducer input shaft speed / main reducer output shaft speed, and transmission system temperature.

[0056] Step 3. Data Processing: In some embodiments, the rotor-related vibration data includes a first frequency and a first amplitude. When the first data includes triaxial airframe vibration acceleration, engine parameters, transmission system operating parameters, and rotor-related vibration data collected by vibration sensors, the frequency and amplitude are calculated based on the first data, including: Select the Z-axis body vibration acceleration from the three-axis body vibration acceleration; The Z-axis machine body vibration acceleration is low-pass filtered; Frequency domain analysis was performed on the filtered Z-axis body vibration acceleration to obtain the second frequency and the second amplitude. The fusion frequency is obtained by fusing the first frequency and the second frequency, and the fusion amplitude is obtained by fusing the first amplitude and the second amplitude.

[0057] Specifically, the triaxial body vibration acceleration data acquired by the IMU is processed in accordance with step 3 of the first embodiment to obtain the second frequency f2 and the second amplitude A2, which will not be elaborated here.

[0058] Then, f1 / f2 is fused to obtain f_fusion, and A1 / A2 is fused to obtain A_fusion. Data fusion can use a fixed weighted average algorithm (e.g., a weight of 0.7 for the vibration sensor and 0.3 for the IMU), but this algorithm requires manually preset weights that remain unchanged throughout the process. Alternatively, it can be replaced with an adaptive fusion algorithm based on the size of the unmanned helicopter, its vibration characteristics, and flight conditions. This algorithm evaluates the signal-to-noise ratio, peak resolution, amplitude stability, and signal reliability of the vibration sensor and IMU signals in real time, dynamically allocating fusion weights for the two signals based on the evaluation results. It uses normalization to ensure the weights sum to 1, increasing the weight of the vibration sensor when its signal quality is high and increasing the IMU weight when the airframe vibration interference is high. This dynamic adaptive adjustment achieves high-precision fusion of vibration frequency and amplitude, improving the robustness and accuracy of emergency speed estimation under different helicopter models and flight conditions.

[0059] Step 4. Speed ​​estimation and verification: The rotor speed is directly calculated based on the formula N = f × 60 ÷ number of blades.

[0060] Then, in some embodiments, it is determined whether the rotor speed needs to be corrected based on the amplitude and the first data. If it is determined that correction is needed, the rotor speed is corrected based on the amplitude, including: Verify the amplitude: determine whether the amplitude is within the amplitude threshold range; Verify the engine speed: determine whether the absolute or relative deviation between the rotor speed and the converted speed of the engine is less than a preset deviation value; Verify the operating parameters: determine whether the transmission system operating parameters and the engine throttle opening or torque command meet the preset requirements; If only the amplitude verification fails, the rotor speed is corrected.

[0061] In some embodiments, correcting the rotor speed includes: The equivalent rotational speed is obtained by converting the engine speed to the nominal transmission ratio. The deviation rate and deviation direction are determined based on the rotor speed and the equivalent rotational speed. The rotor speed is then corrected based on the deviation rate and deviation direction.

[0062] Specifically, triple verification: (1) Amplitude verification: Determine whether A is within the preset threshold range.

[0063] (2) Cross-verification of engine speed: Calculate |N - N_engine| / N. If the deviation value is ≤6%, the transmission system is considered to be normal and N is valid.

[0064] (3) Transmission parameter auxiliary judgment: A comprehensive judgment is made by combining real-time collected parameters such as whether the gear meshing frequency is stable and whether the belt tension is normal. The specific judgment is as follows: 1) Real-time calculation of transmission ratio: The real-time transmission ratio is calculated by dividing the engine speed by the (main reducer input shaft speed / output shaft speed). This ratio is then compared to the theoretical transmission ratio to determine if slippage, breakage, or wear has occurred. For example, a short-term, sustained increase in the real-time transmission ratio indicates slippage; a sharp increase in the real-time transmission ratio indicates belt breakage; and a consistently high real-time transmission ratio with a monotonically increasing trend indicates wear.

[0065] 2) Gear meshing frequency verification: The fundamental and harmonic frequencies of gear meshing are extracted from the vibration signal; compared with the theoretical meshing frequency, gear wear, tooth breakage, and abnormal clearance are determined. For example, if the meshing frequency and its harmonic amplitude rise overall, and the amplitude shows a monotonically increasing trend with running time, it is judged as uniform gear wear; the appearance of obvious rotational frequency and its low-order harmonics is judged as tooth breakage; the appearance of symmetrical or asymmetrical sidebands on both sides of the meshing frequency is judged as abnormal clearance.

[0066] 3) Calculation of belt tension / slippage ratio: Slip ratio S = |(Engine equivalent rotor speed N_engine) Estimate rotor speed (N) / N_engine|×100%. If slip ratio S≤3%, belt tension is normal; if 3%<slip ratio S≤8%, belt is slightly loose; if slip ratio S>8%, belt is severely loose and tension is insufficient, triggering correction and warning.

[0067] 4) Temperature and dynamic parameters auxiliary verification: Transmission system temperature too high (exceeding temperature threshold) → Risk of thermal slippage assessed.

[0068] Engine torque / throttle mismatch with speed → Indicates abnormal power transmission from the engine or throttle.

[0069] Final decision logic: When all three verifications pass, output the estimated N above, which is a high-confidence rotational speed value.

[0070] If only the engine speed verification fails (deviation > 6%), but the amplitude and transmission parameters are normal, then the above-mentioned N based on vibration estimation is accepted, and a "transmission system slippage fault" warning is triggered, because the vibration comes directly from the rotor and is more reliable than the engine calculation.

[0071] If only amplitude verification fails, but no abnormalities are found in engine speed cross-verification and transmission parameter auxiliary judgment, the system further analyzes the harmonic structure of the vibration spectrum: if each harmonic is still an integer multiple of the rotor speed, the frequency interval is stable, and the harmonic amplitude ratio remains basically unchanged, and only the fundamental frequency amplitude increases abnormally, then it is determined to be rotor body imbalance or blade damage, rather than a transmission system fault. At this time, the rotor fault adaptive correction strategy is activated. Under the premise of keeping the vibration estimation frequency unchanged, the calculated rotor speed is dynamically adjusted within a small range according to the degree to which the amplitude exceeds the threshold. The adjustment coefficient is preferentially set to 0.98–1.02, and a rotor imbalance warning is output simultaneously.

[0072] Specifically, the deviation rate between the estimated engine speed N and the engine's equivalent speed Nengine is: δ = |N Nengine∣ / Nengine×100%, combined with the deviation direction ΔN=N Nengine makes a judgment. When δ exceeds ±3%, an enhanced emergency speed correction strategy is activated, which includes: 1) Correction of slight slippage in the transmission system When ΔN < 0 and 3% < δ ≤ 8%, it is determined to be slight slippage in the transmission system. In this case, the mean fusion correction formula is used to suppress deviation while ensuring speed continuity. Ncorrected = (N + Nengine) / 2; 2) Correction of severe slippage in the transmission system When ΔN < 0 and δ > 8%, the transmission system is considered to be severely slipping. In this case, an adaptive constraint correction formula is used, with the engine's equivalent speed as the primary reference, and an adaptive coefficient k is introduced: Ncorrected=Nengine×k (k∈[0.92,1.00]) The value of k is adaptively adjusted according to the slip ratio and transmission temperature: as δ increases, k decreases linearly from 1.00 to 0.92; when δ>12% or the transmission temperature exceeds the limit, k is fixed at 0.92.

[0073] 3) Engine response lag / insufficient power correction When ΔN>0 and δ>3%, it is determined that the engine speed is too low or the response is lag, rather than transmission slippage. In this case, an adaptive compensation correction formula is used: Ncorrected=Nengine×k (k∈[1.00,1.08]); Among them, the value of k increases linearly from 1.00 to 1.08 as δ increases; when δ>12%, k is fixed at 1.08.

[0074] After correction, ensure that the speed deviation is reduced to within ±3%.

[0075] 5. Signal output and switching: In some embodiments, it further includes: Based on the verification results of the three factors, a graded early warning system is established, and graded early warning signals are output.

[0076] Specifically, the tiered early warning system is as follows: ①Highest priority: If the amplitude verification fails and the belt slip rate exceeds the limit, it is determined that the belt is slipping, dynamic speed correction is initiated, and a first-level warning is triggered; ② Transmission chain integrity verification: If the real-time transmission ratio or gear meshing characteristics are abnormal, but the speed deviation is still within an acceptable range, maintain the current emergency speed, reduce its confidence level, and output a level 2 warning. ③ Thermal / Power Safety Verification: If the transmission system temperature exceeds the limit or the engine torque-speed relationship is abnormal, actively reduce the rotor target speed command to limit power output and prevent slippage from worsening; ④ All pass: When the amplitude, engine speed cross-verification, and transmission parameter auxiliary judgment all pass, output a high-confidence emergency speed without triggering additional restrictions.

[0077] The flight control system replaces the failed rotor sensor signal with a valid / corrected rotational speed N. If the rotor speed sensor detects a stable and valid signal for 100ms, it sends a corresponding signal to switch the vibration sensor back to normal acquisition mode. Simultaneously, the flight control system executes a safe flight strategy based on the warning signal.

[0078] It is clearly pointed out that vibration sensors in the prior art are only used for "health monitoring" (post-event diagnosis, maintenance early warning), while the present invention extends its function to "real-time control" (online feedback, process participation). This change in application scenario brings about non-obvious technical effects.

[0079] Compared with the prior art, the emergency judgment method for rotor speed sensor failure of unmanned helicopters provided in this embodiment has the following beneficial effects: 1. Pioneering Application: Breaking through technical biases, it is the first to propose and realize the use of airborne IMU-collected fuselage vibration data for emergency speed estimation after rotor speed sensor failure. The characteristic vibration frequency of the rotor is extracted through a specific signal processing link, fundamentally eliminating the single dependence on the transmission chain.

[0080] 2. Flexible Architecture: A two-tiered flexible technical architecture is proposed, consisting of "IMU standalone estimation" and "IMU + vibration sensor fusion estimation." Basic emergency response can be achieved using the IMU without additional hardware, while adding a vibration sensor can improve accuracy at a low cost. "IMU standalone estimation" enables zero-hardware-cost emergency response capabilities "from scratch"; "IMU + vibration sensor fusion estimation," through weighted fusion algorithms (such as high weighting for vibration sensors) and refined frequency domain analysis, achieves high-precision estimation "from existing to optimal," perfectly adapting to different models from light to heavy-duty. This achieves full coverage of models with different hardware configurations, reduces modification costs, and improves industrial applicability.

[0081] 3. Functional Reuse and Synergy: The vibration sensor achieves dual functionality and synergy with the IMU. Normally, the vibration sensor independently monitors the health of moving parts; in emergencies, it merges with IMU data to form a highly reliable speed estimation source, eliminating the need for additional emergency data acquisition equipment and significantly improving the utilization rate of airborne equipment.

[0082] 4. Intelligent Verification and Diagnosis: A multi-factor verification and correction mechanism based on vibration amplitude threshold, cross-verification of engine converted speed, and auxiliary judgment of transmission system parameters has been constructed. This mechanism can not only output high-precision emergency speed, but also simultaneously diagnose faults such as rotor imbalance and transmission system slippage / wear, and realize safety-level early warning.

[0083] 5. High estimation accuracy: The rotor speed can be directly calculated from the vibration frequency, which can identify transmission faults. The estimation deviation is ≤±1%, which meets the flight control accuracy requirements. 6. Good flight continuity: Quickly switches to emergency mode after rotor speed sensor failure to avoid entering restricted flight and ensure mission execution; 7. High real-time performance: The data acquisition and processing response time is ≤100ms, compatible with existing flight control systems, and does not change the original control logic.

[0084] Example 2, Another embodiment of the present invention discloses an emergency judgment system for rotor speed sensor failure in unmanned helicopters, applied to the flight control system of unmanned helicopters, thereby realizing the emergency judgment method for rotor speed sensor failure in unmanned helicopters in Embodiment 1. The specific implementation of each module is as described in the corresponding description in Embodiment 1, including: Rotor speed sensor failure monitoring module: used to monitor the output signal of the rotor speed sensor in real time and determine whether the rotor speed sensor has failed based on the output signal of the rotor speed sensor; Data acquisition module: Used to acquire the first data if the judgment fails.

[0085] Data processing and fusion module: used to calculate the frequency and amplitude based on the first data; Rotor speed estimation and verification module: used to calculate the rotor speed based on the frequency; when the first data only includes the triaxial body vibration acceleration, it determines whether the rotor speed needs to be corrected based on the amplitude; when the first data includes the triaxial body vibration acceleration, engine parameters, transmission system operating parameters and rotor-related vibration data collected by vibration sensors, it determines whether the rotor speed needs to be corrected based on the amplitude and the first data; if it is determined that correction is needed, the rotor speed is corrected according to the amplitude.

[0086] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware, and the corresponding computer program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0087] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for emergency judgment of rotor speed sensor failure in an unmanned helicopter, characterized in that, The steps include the following: Monitor the output signal of the rotor speed sensor; The rotor speed sensor output signal is used to determine whether the rotor speed sensor is malfunctioning. If it is determined to be malfunctioning, the first data is collected. The frequency and amplitude are calculated based on the first data; The rotor speed is calculated based on the frequency. When the first data only includes the triaxial body vibration acceleration, it is determined whether the rotor speed needs to be corrected based on the amplitude; when the first data includes the triaxial body vibration acceleration, engine parameters, transmission system operating parameters, and rotor-related vibration data collected by vibration sensors, it is determined whether the rotor speed needs to be corrected based on the amplitude and the first data; if it is determined that correction is needed, the rotor speed is corrected according to the amplitude.

2. The emergency judgment method for rotor speed sensor failure of unmanned helicopters according to claim 1, characterized in that, The step of determining whether the rotor speed sensor is malfunctioning based on the output signal of the rotor speed sensor includes: If the interruption time of the rotor speed sensor output signal exceeds a preset time threshold, or if the fluctuation of the rotor speed sensor output signal exceeds a fluctuation threshold and the duration exceeds a preset time threshold, then the rotor speed sensor is determined to be faulty.

3. The emergency judgment method for rotor speed sensor failure of unmanned helicopters according to claim 1, characterized in that, When the first data only includes the triaxial body vibration acceleration, the frequency and amplitude are calculated based on the first data, including: Select the Z-axis body vibration acceleration from the three-axis body vibration acceleration; The Z-axis machine body vibration acceleration is low-pass filtered; Frequency domain analysis was performed on the filtered Z-axis body vibration acceleration to obtain the frequency and amplitude.

4. The emergency judgment method for rotor speed sensor failure of unmanned helicopters according to claim 1, characterized in that, When the first data only includes the vibration acceleration of the three-axis airframe, it is determined whether the rotor speed needs to be corrected based on the amplitude. If it is determined that correction is needed, the rotor speed is corrected based on the amplitude, including: Determine whether the amplitude is within the amplitude threshold range. If it is within the amplitude threshold range, the rotor speed is confirmed to be valid. If it is not within the amplitude threshold range, the rotor speed is confirmed to be abnormal. Determine the correction coefficient based on the amplitude, and multiply the rotor speed by the correction coefficient to obtain the corrected rotor speed.

5. The emergency judgment method for rotor speed sensor failure of unmanned helicopters according to claim 4, characterized in that, Also includes: Collect engine speed; The converted speed is obtained by converting the engine speed according to the nominal transmission ratio. Determine whether the absolute or relative deviation between the rotor speed and the calculated speed is greater than a preset deviation value. If so, output a warning message indicating a possible abnormality in the transmission system.

6. The emergency judgment method for rotor speed sensor failure of unmanned helicopters according to claim 4, characterized in that, Also includes: Based on different situations where the amplitude exceeds the preset amplitude threshold range, graded early warnings are issued and graded early warning signals are output.

7. The emergency judgment method for rotor speed sensor failure of unmanned helicopters according to claim 1, characterized in that, The rotor-related vibration data includes a first frequency and a first amplitude. When the first data includes triaxial fuselage vibration acceleration, engine parameters, transmission system operating parameters, and rotor-related vibration data collected by vibration sensors, the frequency and amplitude are calculated based on the first data, including: Select the Z-axis body vibration acceleration from the three-axis body vibration acceleration; The Z-axis machine body vibration acceleration is low-pass filtered; Frequency domain analysis was performed on the filtered Z-axis body vibration acceleration to obtain the second frequency and the second amplitude. A fusion frequency is obtained by fusing the first frequency and the second frequency, and a fusion amplitude is obtained by fusing the first amplitude and the second amplitude.

8. The emergency judgment method for rotor speed sensor failure of unmanned helicopters according to claim 7, characterized in that, Based on the amplitude and the first data, determine whether the rotor speed needs to be corrected. If it is determined that correction is needed, correct the rotor speed according to the amplitude, including: Verify the amplitude: determine whether the amplitude is within the amplitude threshold range; Verify the engine speed, including the engine parameters: determine whether the absolute or relative deviation between the rotor speed and the converted speed of the engine is less than a preset deviation value; Verify the operating parameters: determine whether the engine throttle opening / torque command, including the transmission system operating parameters and the engine parameters, meets the preset requirements; If only the amplitude verification fails, the rotor speed is corrected.

9. The emergency judgment method for rotor speed sensor failure of unmanned helicopters according to claim 8, characterized in that, Correcting the rotor speed includes: The equivalent rotational speed is obtained by converting the engine speed to the nominal transmission ratio. The deviation rate and deviation direction are determined based on the rotor speed and the equivalent rotational speed. The rotor speed is then corrected based on the deviation rate and deviation direction.

10. An emergency judgment system for rotor speed sensor failure in an unmanned helicopter, characterized in that, include: Rotor speed sensor failure monitoring module: Used to monitor the output signal of the rotor speed sensor and determine whether the rotor speed sensor has failed based on the output signal of the rotor speed sensor; Data acquisition module: Used to acquire the first data if the judgment fails; Data processing and fusion module: used to calculate the frequency and amplitude based on the first data; Rotor speed estimation and verification module: used to calculate the rotor speed based on the frequency; when the first data only includes the triaxial body vibration acceleration, it determines whether the rotor speed needs to be corrected based on the amplitude; when the first data includes the triaxial body vibration acceleration, engine parameters, transmission system operating parameters and rotor-related vibration data collected by vibration sensors, it determines whether the rotor speed needs to be corrected based on the amplitude and the first data; if it is determined that correction is needed, the rotor speed is corrected according to the amplitude.

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