A method and system for channel erasure recovery of a helicopter blade flapping bending moment

Abstract

The application discloses a channel invalid data repairing method and system for oscillation bending moment of a helicopter blade, which comprises the following steps: step 1, determining a test device damaged channel as a target channel; step 2, selecting ordered and discrete data of a test channel at the same spanwise station of a backup test blade as a base sample array, and simultaneously selecting the test channel at the same spanwise station of a main test blade and the backup test blade, and calculating a linear factor array; step 3, performing physical twin processing on the base sample array in step 2 to generate a sub-sample array, multiplying the sub-sample array by the linear factor array, performing dynamic correction on inherent deviation of the sub-sample array, obtaining a target sample array, and assigning elements of the target sample array to the target channel in sequence. The application solves the problem that, in the existing load measurement process of the helicopter blade, the test values of the oscillation bending moment of different blades are deviated, and it is difficult to apply the test values to the calculation of the dynamic response of the rotor blade.

Description

Technical Field

[0001] This invention relates to, but is not limited to, the field of helicopter strength design technology, specifically to a method and system for repairing invalid channel data of helicopter rotor blade flapping moment. Background Technology

[0002] During helicopter rotor blade load measurement and flight testing, the flapping moment of the two rotor blades is usually measured simultaneously to ensure that the flapping moment at each station of the blade is obtained. One blade is the main test blade, and the other is the backup test blade. The arrangement and geometric parameters of the strain gauges at the flapping moment measurement station of the backup blade are consistent with those of the main test blade, and the number of measurement stations may be less than that of the main test blade.

[0003] The generation mechanism of the flapping moment of the rotor blades determines that the flapping moment of these two blades has the following characteristics: Under steady-state conditions, the aerodynamic environment history of the two blades can be considered the same within one rotation of the blade, with only a fixed difference in blade azimuth angle; the flapping moment history generated by the flapping motion of each blade at the same position is similar to the aerodynamic environment history, and the fluctuation pattern, mean, and peak-to-peak value of the flapping moment history of each blade at the same position within the same rotation period are relatively similar; the root cause of the numerical deviation of the flapping moment of different blades mainly comes from inherent deviations in blade manufacturing and assembly, and this numerical deviation is inherent and objectively exists. While the numerical deviation of the flapping moment of different blades is acceptable in the field of fatigue assessment, it is unacceptable for calculating the dynamic response of rotor blades. Summary of the Invention

[0004] The purpose of this invention is to address the aforementioned problems by providing a method and system for repairing invalid channel data of helicopter rotor blade flapping moment. This addresses the issue that existing load measurements of helicopter rotor blades, based on the measurement method of rotor blade flapping moment, result in deviations in the test values ​​of flapping moments for different blades, making them difficult to apply to rotor blade dynamic response calculations.

[0005] The technical solution of the present invention:

[0006] This invention provides a method for repairing invalid channel data related to helicopter rotor blade flapping moment, comprising:

[0007] Step 1: Identify the damaged channel of the test equipment as the target channel (Rc);

[0008] Step 2: Select ordered, discrete data from the test channel (rc) at the same spanwise station in the backup test blade as the base sample array (M). rc Simultaneously select the test channel with the same display station position for the main test blade and the backup test blade, and calculate the linear factor array.

[0009] Step 3, for the base sample array (M) in Step 2 rc Perform physical twinning to generate a subsample array (M) rc＇ ), and multiply the subsample array by the linear factor array (λ). m＇ This performs dynamic correction of the inherent bias of the subsample row array to obtain the target sample row array (M). bm＇ ), the target sample row array (M) bm＇ The elements of ) are assigned to the target channel in sequence.

[0010] Optionally, in the channel invalid data repair method for helicopter rotor blade flapping moment as described above, before step 1, the method further includes:

[0011] Test channels are arranged on the main test blade and backup test blade of the helicopter rotor. The spanwise positions of the multiple test channels arranged on the backup test blade correspond to the spanwise positions of the test channels on the main test blade, and the number of test channels on the main test blade is greater than or equal to the number of test channels on the backup test blade.

[0012] Optionally, in the channel invalid data repair method for helicopter rotor blade flapping moment as described above, step 1 includes:

[0013] Based on the test channel layout for rotor blade flapping moment and the measured time-domain data, the test channel on the main test blade where the data is completely invalid due to damage to the test components is identified as the target channel.

[0014] Optionally, in the channel invalid data repair method for helicopter rotor blade flapping moment as described above, the method for selecting each test channel in step 2 is as follows:

[0015] Step 21: Determine that the data of the test channel at the same spanwise station position corresponding to the target channel in the backup test blade is valid, designate the test channel as the source channel, and define the data of the source channel as source data;

[0016] Step 22: Select another test channel with the same spanwise position for the main test blade and the backup test blade, and whose data is valid, as the dividend channel and the divisor channel, respectively.

[0017] Optionally, in the above-described method for repairing invalid channel data related to helicopter rotor blade flapping moment, the processing of the selected channel in step 2 includes:

[0018] Step 23: Using the rotor blade azimuth and rotational speed signal as the time reference, the time-domain data of the divisor channel, the divisor channel, and the source channel are discretized into N rotation cycles in chronological order.

[0019] Step 24: Use the raw test data from each rotation cycle of the source channel as the base sample array (M)rc );

[0020] Step 25: Calculate the linear factor array (λ) based on the original test data of the dividend channel and divisor channel in each rotation cycle. m＇ ).

[0021] Optionally, in the channel invalid data repair method for helicopter rotor blade flapping moment as described above, step 25 includes:

[0022] Calculate the peak-to-peak values ​​of the time-domain data of the dividend and divisor channels sequentially in each rotation cycle. Divide the peak-to-peak value of the dividend channel by the peak-to-peak value of the divisor channel within the same rotation cycle to obtain the linear factor for the corresponding rotation cycle. Construct a linear factor array (λ) using the linear factors for each rotation cycle. m＇ ), including N linear factors.

[0023] Optionally, in the channel invalid data repair method for helicopter rotor blade flapping moment as described above, step 3 includes:

[0024] Step 31, for the selected base sample array (M) rc Perform hysteresis processing (delay, same order, same amplitude) to generate a subsample array (M). rc＇ );

[0025] Step 32, for the subsample array (M) rc＇ Multiplying this by a linear factor corresponding to the rotation period yields the target sample row array (M). bm＇ The target sample row array is assigned one-to-one to the target channel to construct the discrete digital signal of the target channel.

[0026] This invention also provides a channel invalid data repair system for helicopter rotor blade flapping moment, comprising: a helicopter rotor, test channels arranged on the main test blade and backup test blade of the helicopter rotor, and a memory and a processor;

[0027] Among them, the spanwise positions of the multiple test channels deployed on the backup test blade correspond to the spanwise positions of the test channels on the main test blade, and the number of test channels on the main test blade is greater than or equal to the number of test channels on the backup test blade.

[0028] The memory is configured to store executable instructions;

[0029] The processor is configured to implement, when executing the executable instructions stored in the memory, a channel invalid data repair method for helicopter rotor blade flapping moment as described above.

[0030] The beneficial effects of this invention are:

[0031] This invention provides a method and system for repairing invalid channel data related to helicopter rotor blade flapping moment. The method, based on the inherent characteristics of helicopter rotor blade flapping moment, identifies the damaged channel of the test equipment as the target channel (Rc). It then selects ordered, discrete data from the test channels (rc) at the same spanwise position in the backup test rotor blades as a base sample array (M). rc ); and simultaneously select the test channel at the same display station position for the main test blade and the backup test blade, calculate the linear factor array; and through the base sample array (M rc Perform physical twinning to generate a subsample array (M) rc＇ ), and multiply the subsample array by the linear factor array (λ). m＇ This performs dynamic correction of the inherent bias of the subsample row array to obtain the target sample row array (M). bm＇ ), the target sample row array (M) bm＇ The elements of the array are assigned sequentially to the target channel. The technical solution of this invention introduces a linear factor for data correction to objectively and faithfully reflect the aforementioned numerical deviations.

[0032] Compared to the repair method for invalid data faults in the blade flapping moment channel in the embodiments of the present invention, traditional processing methods mainly have two aspects: one is to directly adopt the measured value of the flapping moment at the same station in the spanwise direction of the backup blade, and the other is to use valid data from other stations of the test blade and interpolate it in different ways. The former does not consider the error caused by the difference in dynamic characteristics of different blades of a rotor under different installation states, while the latter will produce a large error when multiple stations of the same blade have invalid data. Compared with traditional processing methods, the technical solution of the embodiments of the present invention has the following beneficial effects:

[0033] a) By introducing a dynamic linear correction factor, a digital twin repair model for invalid data in the blade flapping moment measurement channel is established, which can reflect the numerical deviation caused by the inherent deviation of different blade structural characteristics to the greatest extent and the repaired data has high fidelity.

[0034] b) Immediacy, enabling real-time data repair, blade flapping moment data processing and analysis during flight tests;

[0035] c) No need to interrupt flight testing, saving development costs. That is, the integrity of blade flapping moment measurement data can be achieved without interruption or extension of the iron bird or flight test cycle, ensuring the orderly completion of real-time monitoring of blade flapping moment data and accurate assessment of structural life in helicopter development, guaranteeing the development cycle and saving development costs. Attached Figure Description

[0036] The accompanying drawings are provided to further understand the technical solutions of the present invention and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of the present invention and do not constitute a limitation on the technical solutions of the present invention.

[0037] Figure 1 This is a schematic diagram of the arrangement and geometric relationship of the flapping moment test channel for the main test blade and backup test blade of the helicopter rotor in an embodiment of the present invention.

[0038] Figure 2 The diagram shown illustrates the repair effect of the channel invalid data repair method using helicopter rotor blade flapping moment in an embodiment of the present invention. Detailed Implementation

[0039] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0040] As explained in the background section, the existing load measurement process for helicopter rotor blades is based on the measurement method of blade flapping moment, which leads to deviations in the test values ​​of flapping moment for different blades, making it difficult to directly apply to the calculation of rotor blade dynamic response.

[0041] The blade flapping moment strain gauges, lead wires, and other measuring components are high-precision measuring components. If any of these components are damaged, the data in the associated test signal channels (hereinafter referred to as "channels") will be completely invalid. If multiple channels of blade flapping moment data are invalid, especially if adjacent channels are invalid, the traditional approach is to use least squares, polynomial, or other interpolation methods to fit the data, or to directly adopt the measured data from the backup blade's same station channel to reconstruct the data for the invalid data channels. However, the above methods do not consider the influence of structural dynamic characteristic deviations between blades due to manufacturing and assembly, which will introduce errors and distort the data.

[0042] To address the existing methods for handling invalid channel data of helicopter rotor blade flapping moment, this invention provides a method and system for repairing invalid channel data of helicopter rotor blade flapping moment. By introducing a linear factor for data correction, the method objectively and faithfully reflects the aforementioned numerical deviations. The technical solution provided by this invention can accurately reflect the numerical deviations caused by the inherent deviations of different rotor blade structural characteristics. It instantly and faithfully repairs invalid data (with backup rotor blade test data valid and the number of channels not exceeding the number of backup rotor blade test channels) caused by damage to test components. This ensures the integrity of rotor blade flapping moment measurement data without interruption or extension of the iron bird or flight test cycle, guaranteeing real-time monitoring of rotor blade flapping moment data and accurate structural life assessment during helicopter development, thus ensuring the development cycle and saving development costs.

[0043] The present invention provides the following specific embodiments, which can be combined with each other. For the same or similar concepts or processes, they may not be described again in some embodiments.

[0044] like Figure 1 The diagram shows the arrangement and geometric relationship of the flapping moment test channels (i.e., test stations) for the main test blade and backup test blade of a helicopter rotor in an embodiment of the present invention. In reality, after numerous workflows including sensor calibration, installation, standardization, data acquisition, and DSP processing, the flapping moment data for each test channel of each test blade is a set of digital signals synchronously sampled and arranged in time sequence, forming a one-dimensional digital array. The number of elements n in this array is determined by the sampling frequency f. s and the length of the data period t being analyzed c Sure.

[0045] The technical approach of the channel invalid data repair method for helicopter rotor blade flapping moment provided in this invention embodiment is as follows: based on the inherent characteristics of helicopter rotor blade flapping moment, it includes the following steps:

[0046] Step 1: Identify the damaged channel of the test equipment as the target channel, and designate the target channel as Rc;

[0047] Step 2: Select ordered, discrete data from the test channel (test channel number rc) at the same spanwise station in the backup test blade as the base sample array (M). rc Simultaneously select the test channel with the same display station position for the main test blade and the backup test blade, and calculate the linear factor array.

[0048] Step 3: Perform physical twinning on the base sample array from Step 2 to generate a sub-sample array (M). rc＇ ), and multiply the subsample array by the linear factor array (λ).m＇ This performs dynamic correction of the inherent bias of the subsample row array to obtain the target sample row array (M). bm＇ Finally, the target sample row array (M) is... bm＇ The elements of ) are assigned to the target channel in sequence.

[0049] The channel invalid data repair method for helicopter rotor blade flapping moment provided in this embodiment of the invention is used to repair damaged channel data. The repaired target channel data and the selected valid channel data are data pairs that are synchronized, in the same order, and have the same elements.

[0050] It should be noted that the channel invalid data repair method for helicopter rotor blade flapping moment provided in this embodiment of the invention has the following two prerequisites:

[0051] 1) The test channel data for the backup test blade corresponding to the spanwise station is valid;

[0052] 2) Data from the test channel at the same spanwise station location is valid when both the main test blade and the backup test blade are present.

[0053] Therefore, before implementing the channel invalid data repair method provided by this invention, it is necessary to arrange a test channel on the propeller blade, specifically including:

[0054] Test channels are arranged on the main test blade and backup test blade of the helicopter rotor. The spanwise positions of the multiple test channels on the backup test blade correspond to the spanwise positions of the test channels on the main test blade, and the number of test channels on the main test blade is greater than or equal to the number of test channels on the backup test blade. For example... Figure 1 The diagram shows the arrangement of the helicopter rotor blade flapping moment test channel.

[0055] The following examples illustrate in detail the implementation of each step of the channel invalid data repair method for helicopter rotor blade flapping moment provided by the present invention.

[0056] Example 1:

[0057] Step 1: Arrange test channels on the main test blade and backup test blade of the helicopter rotor. The spanwise positions of the multiple test channels on the backup test blade correspond to the spanwise positions of the test channels on the main test blade, and the number of test channels on the main test blade is greater than or equal to the number of test channels on the backup test blade. Figure 1 The test channel layout is shown.

[0058] Step 2: Based on the test channel layout and measured time-domain data of the rotor blade flapping moment, determine the test channel on the main test blade where the data is completely invalid due to damage to the test components as the target channel, and the target channel is numbered Rc.

[0059] Step 3: Determine that the data of the test channel at the same spanwise station corresponding to the target channel Rc in the backup test blade is valid, designate the test channel as the source channel, and define the data of the source channel as the source data; and select another test channel at the same spanwise station of the main test blade and the backup test blade, where the data is valid, as the dividend channel and the divisor channel, respectively.

[0060] Step 4: Using the rotor blade azimuth and rotational speed signal as the time reference, the time-domain data of the divisor channel, the divisor channel, and the source channel are discretized into N rotation cycles in chronological order.

[0061] Step 5: Use the raw test data from each rotation cycle of the source channel as the base sample array (M). rc );

[0062] Step 6: Calculate the linear factor array (λ) based on the original test data of the dividend channel and divisor channel in each rotation cycle. m＇ );

[0063] In this step, the peak-to-peak values ​​of the time-domain data of the dividend and divisor channels are calculated sequentially in time for each rotation cycle. The peak-to-peak value of the dividend channel within the same rotation cycle is divided by the peak-to-peak value of the divisor channel to obtain the linear factor within the corresponding rotation cycle. A linear factor array (λ) is constructed using the linear factors within each rotation cycle. m＇ ), including N linear factors.

[0064] Step 7, for the above base sample array (M) rc Perform physical twinning to generate a subsample array (M) rc＇ ), and multiply the subsample array by the linear factor array (λ). m＇ This performs dynamic correction of the inherent bias of the subsample row array to obtain the target sample row array (M). bm＇ ), the target sample row array (M) bm＇ The elements of ) are assigned to the target channel in sequence.

[0065] In this step, the selected base sample array (M) rc Perform hysteresis processing (delay, same order, same amplitude) to generate a subsample array (M). rc＇ ); for subsample arrays (M) rc＇ Multiplying this by a linear factor corresponding to the rotation period yields the target sample row array (M). bm＇ The target sample row array is assigned one-to-one to the target channel to construct the discrete digital signal of the target channel.

[0066] At this point, the digital signals of the target channel and the source channel are completely synchronized and of the same quantity. Thus, the repair of invalid data in the target channel is complete.

[0067] The method for repairing invalid channel data of helicopter rotor blade flapping moment provided in this invention, based on the inherent characteristics of helicopter rotor blade flapping moment, determines the damaged channel of the test equipment as the target channel (Rc); and selects ordered and discrete data from the test channels (rc) of the same spanwise position in the backup test blade as the base sample array (M). rc ); and simultaneously select the test channel at the same display station position for the main test blade and the backup test blade, calculate the linear factor array; and through the base sample array (M rc Perform physical twinning to generate a subsample array (M) rc＇ ), and multiply the subsample array by the linear factor array (λ). m＇ This performs dynamic correction of the inherent bias of the subsample row array to obtain the target sample row array (M). bm＇ ), the target sample row array (M) bm＇ The elements of the array are assigned sequentially to the target channel. The technical solution of this invention introduces a linear factor for data correction to objectively and faithfully reflect the aforementioned numerical deviations.

[0068] Compared to the repair method for invalid data faults in the blade flapping moment channel in the embodiments of the present invention, traditional processing methods mainly have two aspects: one is to directly adopt the measured value of the flapping moment at the same station in the spanwise direction of the backup blade, and the other is to use valid data from other stations of the test blade and interpolate it in different ways. The former does not consider the error caused by the difference in dynamic characteristics of different blades of a rotor under different installation states, while the latter will produce a large error when multiple stations of the same blade have invalid data. Compared with traditional processing methods, the technical solution of the embodiments of the present invention has the following beneficial effects:

[0069] a) By introducing a dynamic linear correction factor, a digital twin repair model for invalid data in the blade flapping moment measurement channel is established, which can reflect the numerical deviation caused by the inherent deviation of different blade structural characteristics to the greatest extent and the repaired data has high fidelity.

[0070] b) Immediacy, enabling real-time data repair, blade flapping moment data processing and analysis during flight tests;

[0071] c) No need to interrupt flight testing, saving development costs. That is, the integrity of blade flapping moment measurement data can be achieved without interruption or extension of the iron bird or flight test cycle, ensuring the orderly completion of real-time monitoring of blade flapping moment data and accurate assessment of structural life in helicopter development, guaranteeing the development cycle and saving development costs.

[0072] Example 2:

[0073] The first step involved setting up seven stations for the flapping moment tests of both the main test blade and the backup test blade of the prototype rotor. Figure 1 As shown. Assume the flapping moment data array M of the R3 channel of the main test blade. R3 The entire time period is invalid, and the R3 channel of the main test propeller is determined as the target channel Rc. Figure 2 The diagram shown illustrates the repair effect of the channel invalid data repair method using helicopter rotor blade flapping moment in an embodiment of the present invention.

[0074] in, D represents the waving moment data signal acquired by the station channel at a certain moment, ka represents the ka-th moment, ka = N × m, and M in the following text r3 M r4 and M R4 All are related to M R3 For details on the meanings of k, a, N, and m in the synchronously collected data array, please refer to step three.

[0075] The second step is to confirm the validity of the flapping moment data of the backup blade's r3 channel, and then determine the backup blade's r3 channel as the source channel, with its digital signal denoted as the base sample array M. r3 Valid; similarly, determine the flapping moment data M of the main test blade's R4 channel and the backup blade's r4 channel. R4 and M r4 Valid, where channel R4 is the dividend channel and channel r4 is the divisor channel. See appendix. Figure 2 .

[0076] The third step involves using the rotor blade azimuth and rotational speed signal Ψ as the time reference, and discretizing the time-domain data of the remaining three channels, R4, r3, and r4, into N rotation cycles, where N is equal to the measured data time length t. c The integer value obtained after dividing by the blade operating speed Ω. Each rotation cycle contains m raw test data points, where m is determined by the sampling frequency f. s t c And Ω is determined. For example, M R4 Use M R4ka Let represent , where k = 1, 2, ..., N; a = 1, 2, ..., m.

[0077] Fourth step, calculate M R4 and M r4 Peak-to-peak value of the channel's time-domain data in each rotation cycle and and All are positive values.

[0078] in, In the formula, tt represents the peak-to-peak value of the flapping moment data signal collected by the station channel within a certain rotation cycle of the blade.

[0079] Fifth step: Calculate the linear factor one-dimensional sequence λ, which has N elements. k equal remove The value obtained.

[0080] Where, λ=[λ1 λ2 … λ N ].

[0081] Step 6, M r3 The raw test data in each channel rotation cycle is used as the base sample array (Mrc) and physical twinned to obtain the subsample array of the target channel data.

[0082] Step 7: Multiply the subsample array obtained in the previous step by the linear factor corresponding to the rotation period number, and reassign it one-to-one to the target channel data array M. R3 Channel, construct M R3 Channel discrete digital signal M R3ka This is expressed in formula (1), where M is... R3 Digital signals of the channel and M R4 The digital signals in the channel are perfectly synchronized and of the same quantity. This completes the M... R3 Repairing invalid data with intact channel data is shown in the appendix. Figure 2 .

[0083] M R3ka =M r3ka ×λT(k=1,2,…,N; a=1,2,…,m).

[0084] Based on the method for repairing invalid channel data of helicopter blade flapping moment provided in the above embodiments of the present invention, the present invention also provides a system for repairing invalid channel data of helicopter blade flapping moment. The system includes: a helicopter rotor, test channels arranged on the main test blade and backup test blade of the helicopter rotor, as well as a memory and a processor.

[0085] Among them, the spanwise positions of the multiple test channels deployed on the backup test blade correspond to the spanwise positions of the test channels on the main test blade, and the number of test channels on the main test blade is greater than or equal to the number of test channels on the backup test blade.

[0086] The memory is configured to hold executable instructions;

[0087] The processor is configured to implement a channel invalid data repair method for helicopter rotor blade flapping moment as provided in any of the above embodiments when executing the executable instructions stored in the memory.

[0088] While the embodiments disclosed in this invention are as described above, they are merely illustrative of the embodiments to facilitate understanding of the invention and are not intended to limit the invention. Any person skilled in the art to which this invention pertains may make any modifications and variations in the form and details of the implementation without departing from the spirit and scope disclosed herein; however, the scope of patent protection for this invention shall still be determined by the scope defined in the appended claims.

Claims

1. A method for repairing invalid channel data caused by helicopter rotor blade flapping moment, characterized in that, include: Step 1: Identify the damaged channel of the test equipment as the target channel (Rc); Step 2: Select ordered, discrete data from the test channel (rc) at the same spanwise station in the backup test blade as the base sample array (M). rc Simultaneously select the test channel with the same display station position for the main test blade and the backup test blade, and calculate the linear factor array. Step 3, for the base sample array (M) in Step 2 rc Perform physical twinning to generate a subsample array (M) rc＇ ), and multiply the subsample array by the linear factor array (λ). m＇ This performs dynamic correction of the inherent bias of the subsample row array to obtain the target sample row array (M). bm＇ ), the target sample row array (M) bm＇ The elements of ) are assigned to the target channel in sequence.

2. The method for repairing invalid channel data due to helicopter rotor blade flapping moment according to claim 1, characterized in that, Before step 1, the following are also included: Test channels are arranged on the main test blade and backup test blade of the helicopter rotor. The spanwise positions of the multiple test channels arranged on the backup test blade correspond to the spanwise positions of the test channels on the main test blade, and the number of test channels on the main test blade is greater than or equal to the number of test channels on the backup test blade.

3. The method for repairing invalid channel data due to helicopter rotor blade flapping moment according to claim 1, characterized in that, Step 1 includes: Based on the test channel layout for rotor blade flapping moment and the measured time-domain data, the test channel on the main test blade where the data is completely invalid due to damage to the test components is identified as the target channel.

4. The method for repairing invalid channel data due to helicopter rotor blade flapping moment according to claim 3, characterized in that, The method for selecting each test channel in step 2 is as follows: Step 21: Determine that the data of the test channel at the same spanwise station position corresponding to the target channel in the backup test blade is valid, designate the test channel as the source channel, and define the data of the source channel as source data; Step 22: Select another test channel with the same spanwise position for the main test blade and the backup test blade, and whose data is valid, as the dividend channel and the divisor channel, respectively.

5. The method for repairing invalid channel data due to helicopter rotor blade flapping moment according to claim 4, characterized in that, The methods for processing the selected channel in step 2 include: Step 23: Using the rotor blade azimuth and rotational speed signal as the time reference, the time-domain data of the divisor channel, the divisor channel, and the source channel are discretized into N rotation cycles in chronological order. Step 24: Use the raw test data from each rotation cycle of the source channel as the base sample array (M) rc ); Step 25: Calculate the linear factor array (λ) based on the original test data of the dividend channel and divisor channel in each rotation cycle. m＇ ).

6. The method for repairing invalid channel data of helicopter rotor blade flapping moment according to claim 5, characterized in that, Step 25 includes: Calculate the peak-to-peak values ​​of the time-domain data of the dividend and divisor channels sequentially in each rotation cycle. Divide the peak-to-peak value of the dividend channel by the peak-to-peak value of the divisor channel within the same rotation cycle to obtain the linear factor for the corresponding rotation cycle. Construct a linear factor array (λ) using the linear factors for each rotation cycle. m＇ ), including N linear factors.

7. The method for repairing invalid channel data of helicopter rotor blade flapping moment according to claim 6, characterized in that, Step 3 includes: Step 31, for the selected base sample array (M) rc Perform hysteresis processing (delay, same order, same amplitude) to generate a subsample array (M). rc＇ ); Step 32, for the subsample array (M) rc＇ Multiplying this by a linear factor corresponding to the rotation period yields the target sample row array (M). bm＇ The target sample row array is assigned one-to-one to the target channel to construct the discrete digital signal of the target channel.

8. A channel invalid data repair system for helicopter rotor blade flapping moment, characterized in that, include: The helicopter rotor, the test channels arranged on the main test blade and the backup test blade of the helicopter rotor, as well as the memory and processor; Among them, the spanwise positions of the multiple test channels deployed on the backup test blade correspond to the spanwise positions of the test channels on the main test blade, and the number of test channels on the main test blade is greater than or equal to the number of test channels on the backup test blade. The memory is configured to store executable instructions; The processor is configured to implement the channel invalid data repair method for helicopter rotor blade flapping moment as described in any one of claims 1 to 7 when executing the executable instructions stored in the memory.

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