CN115183861A - Dynamic self-noise measurement method and system for MHD micro-angle vibration sensor - Google Patents

Abstract

The present disclosure provides a dynamic self-noise measurement method and system for an MHD micro-angular vibration sensor, the method comprising: receiving an excitation analog signal sequence by using a controller, wherein the excitation analog signal is obtained by converting a target mixing excitation signal sequence by using a signal conversion module; responding to the excitation analog signal sequence, the controller controls the angular vibration table to vibrate, so that an environmental vibration sensor fixedly connected with the angular vibration table and an MHD micro angular vibration sensor coaxially and fixedly connected with the angular vibration table synchronously vibrate; in response to vibration, the MHD micro-angular vibration sensor generates a first vibration signal, the angular vibration table generates a second vibration signal, and the environmental vibration sensor generates a third vibration signal; and determining a time domain dynamic self-noise sequence and a frequency domain dynamic self-noise power spectral density of the MHD micro-angular vibration sensor according to the first vibration signal, the second vibration signal and the third vibration signal.

Description

Dynamic self-noise measurement method and system for MHD micro-angle vibration sensor

technical field

The present disclosure relates to the field of sensor technology, and more particularly, to a dynamic self-noise measurement method, system, electronic device, computer-readable storage medium and computer program product of an MHD micro-angle vibration sensor.

Background technique

With the rapid development of spacecraft, especially high-precision spacecraft represented by high-resolution earth observation remote sensing satellites, deep space exploration remote sensing spacecraft, and deep space laser communication satellites, they are extremely sensitive to the effects of micro-vibration disturbances. The problem of micro-vibration disturbance has become a major factor limiting the further improvement of the precision and stability of high-precision spacecraft attitude control.

Magneto Hydro Dynamics (MHD) micro-angle vibration sensor has the characteristics of low noise, wide frequency band, miniaturization, long life, etc., and is not sensitive to acceleration shock. It can measure broadband micro-angle from several Hz to 1,000 Hz. Vibration information has become the most direct, effective and reliable instrument for measuring spacecraft and payload micro-angular vibration information in orbit.

The output signal of the MHD micro-angle vibration sensor during normal operation can be divided into three parts according to the source: the effective signal associated with the input angle vibration excitation, the external environment interference signal and the self-noise signal. The angular vibration resolution limit is one of the key indicators to measure the performance of the sensor. In the absence of external environmental interference (such as unknown vibration, etc.), it is determined by the sensor's output self-noise and scale factor. Therefore, the accurate measurement of the output self-noise is of great significance for the performance evaluation of the sensor.

During the process of realizing the concept of the present disclosure, the inventors found that there are at least the following problems in the related art: the measurement results of the dynamic self-noise measurement of the MHD micro-angle vibration sensor are less accurate.

SUMMARY OF THE INVENTION

In view of this, embodiments of the present disclosure provide a dynamic self-noise measurement method, system, electronic device, computer-readable storage medium, and computer program product of an MHD micro-angle vibration sensor.

An aspect of the embodiments of the present disclosure provides a method for measuring dynamic self-noise of an MHD micro-angle vibration sensor, including:

Utilize the controller to receive the excitation analog signal sequence, wherein the excitation analog signal is obtained by converting the target mixing excitation signal sequence by using the signal conversion module;

In response to the above-mentioned excitation simulation signal sequence, the above-mentioned controller controls the angular vibration table to vibrate, so that the environmental vibration sensor fixed to the above-mentioned angular vibration table and the above-mentioned MHD micro-angle vibration sensor fixed to the above-mentioned angular vibration table synchronously occur. vibration;

In response to the above-mentioned vibration, the above-mentioned MHD micro-angle vibration sensor generates a first vibration signal, the above-mentioned angular vibration table generates a second vibration signal, and the above-mentioned environmental vibration sensor generates a third vibration signal;

According to the first vibration signal, the second vibration signal and the third vibration signal, the time-domain dynamic self-noise sequence and the frequency-domain dynamic self-noise power spectral density of the MHD micro-angle vibration sensor are determined.

According to an embodiment of the present disclosure, the time-domain dynamic self-noise sequence and the frequency-domain dynamic self-noise power spectral density of the MHD micro-angle vibration sensor are determined according to the first vibration signal, the second vibration signal, and the third vibration signal. ,include:

Calculate the first amplitude squared coherence function and the second amplitude squared coherence function according to the first vibration signal, the second vibration signal and the third vibration signal, wherein the first amplitude squared coherence function is based on the first amplitude squared coherence function. A vibration signal and the above-mentioned second vibration signal are determined, and the above-mentioned second amplitude square coherence function is determined according to the above-mentioned first vibration signal and the third vibration signal output by the environmental vibration sensor;

According to the effective excitation frequency in the above-mentioned first amplitude squared coherence function and the environmental interference frequency in the above-mentioned second amplitude squared coherence function, construct the effective signal and the environmental interference signal respectively;

The time-domain dynamic self-noise sequence and the frequency-domain dynamic self-noise power spectral density are determined according to the first vibration signal, the effective signal, and the environmental interference signal.

According to an embodiment of the present disclosure, before calculating the first amplitude squared coherence function and the second amplitude squared coherence function, the method further includes:

Respectively remove the DC bias signal in the above-mentioned first vibration signal, the above-mentioned second vibration signal and the above-mentioned third vibration signal to obtain the pre-processed first vibration signal, the pre-processed second vibration signal and the pre-processed No. 1 vibration signal. Three vibration signals.

According to an embodiment of the present disclosure, obtaining the first amplitude squared coherence function and the second amplitude squared coherence function according to the first vibration signal, the second vibration signal, and the third vibration signal output by the environmental vibration sensor, including:

For any one of the second vibration signal and the third vibration signal, according to the signal, the total length of the signal, and the preprocessed first vibration signal, determine the first transition function and the second corresponding to the signal. transition function;

According to the first transition function, the second transition function and the third transition function corresponding to the preprocessed first vibration signal, determine the first amplitude squared coherence function or the second amplitude corresponding to the signal Square coherence function.

According to the embodiment of the present disclosure, the above-mentioned construction of the effective signal and the environmental interference signal according to the effective excitation frequency in the above-mentioned first amplitude squared coherence function and the environmental interference frequency in the above-mentioned second amplitude squared coherence function, respectively, includes:

Based on the first preset threshold and the second preset threshold, respectively, the above-mentioned effective excitation frequency corresponding to the above-mentioned first amplitude squared coherence function is obtained from the above-mentioned first amplitude squared coherence function and the above-mentioned second amplitude squared coherence function. and the above-mentioned environmental interference frequency of the above-mentioned second amplitude squared coherence function;

For any coherence function in the first amplitude squared coherence function and the second amplitude squared coherence function, the transition amplitude and transition phase are determined according to the first vibration signal and the intermediate function value, wherein the intermediate function value is based on Determined by the above-mentioned effective excitation frequency or the above-mentioned environmental interference frequency corresponding to the above-mentioned coherence function;

constructing the above-mentioned effective signal according to the above-mentioned transition amplitude and the above-mentioned transition phase corresponding to the above-mentioned first amplitude squared coherence function;

The above-mentioned environmental interference signal is constructed according to the above-mentioned transition amplitude and the above-mentioned transition phase corresponding to the above-mentioned second amplitude squared coherence function.

According to an embodiment of the present disclosure, determining the time-domain dynamic self-noise sequence and the frequency-domain dynamic self-noise power spectral density according to the above-mentioned first vibration signal, the above-mentioned effective signal, and the above-mentioned environmental interference signal includes:

Eliminate the above-mentioned effective signal and the above-mentioned environmental interference signal from the above-mentioned first vibration signal to obtain the above-mentioned time-domain dynamic self-noise sequence;

According to the above-mentioned time-domain dynamic self-noise sequence and the total length of the signal, the above-mentioned frequency-domain dynamic self-noise power spectral density is determined.

According to an embodiment of the present disclosure, the above-mentioned determination of the above-mentioned frequency-domain dynamic self-noise power spectral density according to the above-mentioned time-domain dynamic self-noise sequence and the total length of the signal includes:

According to the time-domain dynamic self-noise sequence, the second vibration signal and the third vibration signal, a new first amplitude squared coherence function and a new second amplitude squared coherence function are determined, wherein the new first amplitude The squared coherence function is determined according to the above-mentioned time-domain dynamic self-noise sequence and the above-mentioned second vibration signal, and the above-mentioned new second amplitude squared coherence function is based on the above-mentioned time-domain dynamic self-noise sequence and the third vibration signal output by the environmental vibration sensor definite;

Based on the first preset threshold and the second preset threshold, the new first amplitude squared coherence function and the new second amplitude squared coherence function are compared respectively, and a comparison result is obtained, wherein the comparison result represents Whether there is a new valid signal in the above-mentioned new first amplitude squared coherence function, and/or whether there is a new environmental interference signal in the above-mentioned new second amplitude squared coherence function;

In the case that the above-mentioned comparison result indicates that the above-mentioned new effective signal and the above-mentioned new environmental interference signal do not exist, the above-mentioned frequency-domain dynamic self-noise power spectral density is determined according to the above-mentioned time-domain dynamic self-noise sequence and the above-mentioned total length of the signal;

When the above comparison result indicates that at least one of the above-mentioned new effective signal and the above-mentioned new environmental interference signal exists, the above-mentioned time-domain dynamic self-noise sequence is determined as a new first vibration signal for using the above-mentioned new A new first amplitude squared coherence function and a new second amplitude squared coherence function are calculated for the first vibration signal.

According to an embodiment of the present disclosure, the dynamic self-noise measurement method of the MHD micro-angle vibration sensor further includes:

Based on the bandwidth of the above-mentioned MHD micro-angle vibration sensor, a plurality of cosine signals with different signal parameters are generated, wherein the above-mentioned signal parameters include at least one of the following: amplitude, frequency and phase;

Based on the sampling frequency of the cosine signal, generate a plurality of initial mixing excitation signal sequences according to the plurality of cosine signals;

Based on a preset range, according to the peak factor of each of the initial frequency mixing excitation signal sequences, the target frequency mixing excitation signal sequence is determined from the plurality of initial frequency mixing excitation signal sequences, wherein the peak factor is determined according to the initial frequency mixing excitation signal sequence. The signal peak value and power of the excitation signal sequence are determined.

Another aspect of the embodiments of the present disclosure provides a dynamic self-noise measurement system of an MHD micro-angle vibration sensor, including:

The signal conversion module is used to convert the received target mixing excitation signal sequence into excitation analog signal;

The controller is used to receive the above-mentioned excitation analog signal sequence, and in response to the above-mentioned excitation analog signal sequence, control the vibration of the angular vibration table

The above-mentioned angular vibration table is used to vibrate under the control of the above-mentioned controller, and outputs the second vibration signal in response to the above-mentioned vibration;

The above-mentioned MHD micro-angle vibration sensor is coaxially fixed with the table top of the above-mentioned angular vibration table, and is used to vibrate synchronously when the above-mentioned angular vibration table vibrates, and in response to the above-mentioned vibration, the first vibration signal is output;

The environmental vibration sensor is fixedly connected with the base of the above-mentioned angular vibration table, and is used to vibrate synchronously when the above-mentioned angular vibration table vibrates, and in response to the above-mentioned vibration, the third vibration signal is output;

The calculation module is configured to determine the time-domain dynamic self-noise sequence and the frequency-domain dynamic self-noise power spectral density of the MHD micro-angle vibration sensor according to the first vibration signal, the second vibration signal and the third vibration signal.

According to an embodiment of the present disclosure, the dynamic self-noise measurement system of the MHD micro-angle vibration sensor further includes:

Industrial computer, which is used to perform the following operations:

Based on the bandwidth of the above-mentioned MHD micro-angle vibration sensor, a plurality of cosine signals with different signal parameters are generated, wherein the above-mentioned signal parameters include at least one of the following: amplitude, frequency and phase;

Based on the sampling frequency of the cosine signal, generate a plurality of initial mixing excitation signal sequences according to the plurality of cosine signals;

Based on a preset range, according to the peak factor of each of the initial frequency mixing excitation signal sequences, the target frequency mixing excitation signal sequence is determined from the plurality of initial frequency mixing excitation signal sequences, wherein the peak factor is determined according to the initial frequency mixing excitation signal sequence. The signal peak value and power of the excitation signal sequence are determined.

Another aspect of the embodiments of the present disclosure provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more programs Multiple processors, when executed, cause the one or more processors to implement the method as described above.

Another aspect of embodiments of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, which when executed, are used to implement the method as described above.

Another aspect of embodiments of the present disclosure provides a computer program product comprising computer-executable instructions that, when executed, are used to implement the method as described above.

According to an embodiment of the present disclosure, the time-domain dynamic self-noise of the MHD micro-angle vibration sensor is calculated by using the first vibration signal of an MHD micro-angle vibration sensor, combining the second vibration signal of the angular vibration and the third vibration signal of the environmental vibration sensor Sequence and frequency domain dynamic self-noise power spectral density, avoiding the problem of large error in test results caused by the introduction of other auxiliary MHD micro-angle vibration sensors and using prior knowledge, and improving the measurement accuracy of the dynamic self-noise of MHD micro-angle vibration sensors Spend.

Description of drawings

The above and other objects, features and advantages of the present disclosure will become more apparent from the following description of embodiments of the present disclosure with reference to the accompanying drawings, in which:

FIG. 1 schematically shows a flowchart of a dynamic self-noise measurement method of an MHD micro-angle vibration sensor according to an embodiment of the present disclosure;

FIG. 2 schematically shows a flow chart of a method for determining a time-domain dynamic self-noise sequence and a frequency-domain dynamic self-noise power spectral density according to an embodiment of the present disclosure;

FIG. 3 schematically shows a result schematic diagram A of the coherence coefficient according to an embodiment of the present disclosure;

FIG. 4 schematically shows a schematic diagram B of a result of the coherence coefficient according to an embodiment of the present disclosure;

FIG. 5 schematically shows a schematic diagram of the results of a time-domain dynamic self-noise sequence and a frequency-domain dynamic self-noise power spectral density according to an embodiment of the present disclosure;

6 schematically illustrates a block diagram of a dynamic self-noise measurement system of an MHD micro-angular vibration sensor according to an embodiment of the present disclosure; and

Figure 7 schematically shows a block diagram of an electronic device suitable for implementing the method described above, according to an embodiment of the present disclosure.

Detailed ways

Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood, however, that these descriptions are exemplary only, and are not intended to limit the scope of the present disclosure. In the following detailed description, for convenience of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. It will be apparent, however, that one or more embodiments may be practiced without these specific details. Also, in the following description, descriptions of well-known structures and techniques are omitted to avoid unnecessarily obscuring the concepts of the present disclosure.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the present disclosure. The terms "comprising", "comprising" and the like as used herein indicate the presence of stated features, steps, operations and/or components, but do not preclude the presence or addition of one or more other features, steps, operations or components.

All terms (including technical and scientific terms) used herein have the meaning as commonly understood by one of ordinary skill in the art, unless otherwise defined. It should be noted that terms used herein should be construed to have meanings consistent with the context of the present specification and should not be construed in an idealized or overly rigid manner.

Where expressions like "at least one of A, B, and C, etc.," are used, they should generally be interpreted in accordance with the meaning of the expression as commonly understood by those skilled in the art (eg, "has A, B, and C") At least one of the "systems" shall include, but not be limited to, systems with A alone, B alone, C alone, A and B, A and C, B and C, and/or A, B, C, etc. ).

FIG. 1 schematically shows a flowchart of a dynamic self-noise measurement method of an MHD micro-angle vibration sensor according to an embodiment of the present disclosure.

As shown in FIG. 1 , the dynamic self-noise measurement method of the MHD micro-angle vibration sensor may include operations S101 ˜ S104 .

In operation S101, the controller receives the excitation analog signal sequence, wherein the excitation analog signal is obtained by converting the target frequency mixing excitation signal sequence by using the signal conversion module.

In operation S102, in response to the excitation simulation signal sequence, the controller controls the angular vibration table to vibrate, so that the environmental vibration sensor fixed to the angular vibration table and the MHD micro-angular vibration sensor fixed to the angular vibration table synchronously vibrate .

In operation S103, in response to the vibration, the MHD micro-angular vibration sensor generates a first vibration signal, the angular vibration table generates a second vibration signal, and the ambient vibration sensor generates a third vibration signal.

In operation S104, the time-domain dynamic self-noise sequence and the frequency-domain dynamic self-noise power spectral density of the MHD micro-angle vibration sensor are determined according to the first vibration signal, the second vibration signal and the third vibration signal.

According to an embodiment of the present disclosure, the target frequency mixing excitation signal sequence may include K cosine signals with different performance parameters, and the target frequency mixing excitation signal sequence Ω(n) is generated by accumulation. In an exemplary embodiment, the performance parameter may be frequency, and the frequencies of the K cosine signals cover the bandwidth of the MHD micro-angle vibration sensor.

According to an embodiment of the present disclosure, the signal conversion module may be a conversion module with a digital-to-analog converter (DAC) and a low-pass filter (LPF), which can convert a target hybrid of the type electrical signal transmitted from the USB bus The frequency excitation signal sequence Ω(n) is converted into a digital excitation analog signal sequence Ω(t), where n=1...N, N is the total number of sampling points, n represents the number of sampling points, and the sampling frequency F _s is selected as the measured The preset multiple of the working bandwidth of the MHD micro-angle vibration sensor, for example, the working bandwidth of the MHD micro-angle vibration sensor is 1 Hz to 1 kHz, and the sampling frequency F _s can be 10 times the working frequency.

According to the embodiment of the present disclosure, the angular vibrating table receives the excitation analog signal sequence Ω(t), drives the angular vibrating table to output angular vibration to generate the second vibration signal u _T (n), and the angular vibrating table drives the coaxial rigidly fixed The measured MHD micro-angle vibration sensor inputs the mixing angular vibration excitation for the MHD micro-angle vibration sensor, thereby generating the first vibration signal u _MHD (n); the environmental vibration sensor rigidly fixed on the base of the angular vibration table can detect Vibration in the environment interferes with the signal, thereby generating a third vibration signal u _INF (n).

According to an embodiment of the present disclosure, the time domain dynamics of the MHD micro-angle vibration sensor is determined by using the acquired first vibration signal u _MHD (n), second vibration signal u _T (n) and third vibration signal u _INF (n) Self-noise sequence and frequency-domain dynamic self-noise power spectral density.

According to the embodiments of the present disclosure, by obtaining the time-domain dynamic self-noise sequence and the frequency-domain dynamic self-noise power spectral density of the MHD micro-angle vibration sensor, its performance can be evaluated to meet the requirements of the MHD micro-angle vibration sensor under the large-scale input range. accurate test of dynamic self-noise.

According to an embodiment of the present disclosure, the time-domain dynamic self-noise of the MHD micro-angle vibration sensor is calculated by using the first vibration signal of an MHD micro-angle vibration sensor, combining the second vibration signal of the angular vibration and the third vibration signal of the environmental vibration sensor Sequence and frequency domain dynamic self-noise power spectral density, avoiding the problem of large error in test results caused by the introduction of other auxiliary MHD micro-angle vibration sensors and using prior knowledge, and improving the measurement accuracy of the dynamic self-noise of MHD micro-angle vibration sensors Spend.

FIG. 2 schematically shows a flowchart of a method for determining a time-domain dynamic self-noise sequence and a frequency-domain dynamic self-noise power spectral density according to an embodiment of the present disclosure.

As shown in FIG. 2 , according to the first vibration signal, the second vibration signal and the third vibration signal, determining the time-domain dynamic self-noise sequence and the frequency-domain dynamic self-noise power spectral density of the MHD micro-angle vibration sensor may include operations S201 ~ Operation S204.

In operation S201, a first amplitude squared coherence function and a second amplitude squared coherence function are calculated according to the first vibration signal, the second vibration signal and the third vibration signal, wherein the first amplitude squared coherence function is based on the first amplitude squared coherence function. The vibration signal and the second vibration signal are determined, and the second amplitude square coherence function is determined according to the first vibration signal and the third vibration signal output by the environmental vibration sensor.

In operation S202, an effective signal and an environmental interference signal are respectively constructed according to the effective excitation frequency in the first amplitude squared coherence function and the environmental interference frequency in the second amplitude squared coherence function.

In operation S203, the time-domain dynamic self-noise sequence and the frequency-domain dynamic self-noise power spectral density are determined according to the first vibration signal, the effective signal, and the environmental interference signal.

According to the embodiment of the present disclosure, both the effective excitation frequency and the environmental interference frequency are obtained by filtering from the corresponding first amplitude squared coherence function or the second amplitude squared coherence function by setting a filtering threshold.

According to the embodiment of the present disclosure, the non-linear least squares method is used to calculate the cosine signal amplitude and phase of the effective excitation frequency and the environmental disturbance frequency, and according to the extracted transition amplitude and transition phase, the effective signal y _MT (n) is constructed and the environmental interference signal y _MI (n), so as to determine the time domain dynamic self-noise sequence and the frequency domain dynamic according to the first vibration signal u _MHD (n), the effective signal y _MT (n) and the environmental interference signal y _MI (n) Self-noise power spectral density.

According to an embodiment of the present disclosure, before calculating the first amplitude squared coherence function and the second amplitude squared coherence function, the following operations may be further included:

The DC bias signals in the first vibration signal, the second vibration signal and the third vibration signal are respectively removed to obtain the preprocessed first vibration signal (y _MHD (n)) and the preprocessed second vibration signal (y _T (n)) and the preprocessed third vibration signal (y _INF (n)).

According to the embodiment of the present disclosure, since the DC bias signal existing in the first vibration signal, the second vibration signal, and the third vibration signal may affect the measurement accuracy of dynamic self-noise, the above three vibration signals can be removed. DC bias in the signal to further improve the measurement accuracy of dynamic self-noise.

According to an embodiment of the present disclosure, the pre-processed first vibration signal y _MHD (n), the pre-processed second vibration signal y _T (n) and the pre-processed third vibration signal y T (n) obtained after removing the DC bias signal are used. The vibration signal y _INF (n) calculates the first magnitude squared coherence function and the second magnitude squared coherence function, thereby determining the time-domain dynamic self-noise sequence and the frequency-domain dynamic self-noise power spectral density.

According to an embodiment of the present disclosure, obtaining the first amplitude squared coherence function and the second amplitude squared coherence function according to the first vibration signal, the second vibration signal, and the third vibration signal output by the environmental vibration sensor may include the following operations:

For any one of the second vibration signal and the third vibration signal, according to the signal, the total length of the signal (N) and the preprocessed first vibration signal, determine the first transition function (G _i (f )) and the second transition function (G _αβ (f)).

或第二幅值平方相干函数

According to the first transition function, the second transition function and the third transition function corresponding to the preprocessed first vibration signal, determine the first amplitude squared coherence function corresponding to the signal

or the second magnitude squared coherence function

In an exemplary embodiment, the DC offset signals in the 100s sampling signals u _MHD (n), u _T (n) and u _INF (n) are removed according to formula (1) to obtain y _MHD (n) respectively , y _T (n) and y _INF (n), where MHD, T and INF represent MHD micro-angle vibration sensor, angular vibration table and environmental vibration sensor respectively, mean represents the mean value of 100s signal, MHD, T and INF are abbreviated as M respectively , T, I.

y _i =u _i -mean(u _i ), i=MHD, T, INF. (1)

According to an embodiment of the present disclosure, the first transition function G _i (f) and the second transition function G _αβ (f) of each signal are calculated according to formulas (2) and (3), respectively.

where f represents the frequency of the signal.

或第二幅值平方相干函数

其中，第一幅值平方相干函数

如公式(4)所示，第二幅值平方相干函数

如公式(5)所示。According to an embodiment of the present disclosure, the first transition function G _i (f), the second transition function G _αβ (f) and the third transition function G _M corresponding to the preprocessed first vibration signal are obtained according to each signal. (f), determine the first amplitude squared coherence function corresponding to the signal

or the second magnitude squared coherence function

where the first magnitude squared coherence function

As shown in equation (4), the second magnitude squared coherence function

As shown in formula (5).

According to an embodiment of the present disclosure, according to the effective excitation frequency in the first amplitude squared coherence function and the environmental interference frequency in the second amplitude squared coherence function, respectively constructing the effective signal and the environmental interference signal may include the following operations:

Based on the first preset threshold and the second preset threshold, respectively, the effective excitation frequency and the second amplitude corresponding to the first amplitude squared coherence function are obtained from the first amplitude squared coherence function and the second amplitude squared coherence function. Ambient disturbance frequency for the value squared coherence function.

For any one of the first amplitude squared coherence function and the second amplitude squared coherence function, the transition amplitude and transition phase are determined according to the first vibration signal and the intermediate function value, wherein the intermediate function value is determined according to the coherence function The corresponding effective excitation frequency or environmental interference frequency is determined.

A valid signal is constructed from the transition amplitude and transition phase corresponding to the first magnitude squared coherence function. The ambient interference signal is constructed from the transition amplitude and transition phase corresponding to the second amplitude squared coherence function.

和第二预设阈值

是人为根据具体被测的MHD微角振动传感器确定的。According to an embodiment of the present disclosure, the first preset threshold

and the second preset threshold

It is artificially determined according to the specific measured MHD micro-angle vibration sensor.

和第二预设阈值

分别筛选出有效激励频率f_Tk和环境干扰频率f_Ik，分别如公式(6)和(7)式表示，其中f_Tk表示第k个有效激励频率，共有K_T个，f_Ik表示第k个环境干扰频率，共有K_I个。According to an embodiment of the present disclosure, according to the set first preset threshold

and the second preset threshold

Filter out the effective excitation frequency f _Tk and the environmental interference frequency f _Ik respectively, which are expressed as formulas (6) and (7) respectively, where f _Tk represents the kth effective excitation frequency, there are K _T in total, and f _Ik represents the kth There are K _I frequencies of environmental interference.

According to the embodiment of the present disclosure, the effective excitation frequency f _Tk and the environmental interference frequency f _Ik may respectively construct a matrix.

其中，W_*k是根据有效激励频率f_Tk或环境干扰频率f_Ik的矩阵确定的，同时可以将预处理后的第一振动信号y_MHD(n)写为一个列向量。According to an embodiment of the present disclosure, according to the nonlinear least squares method shown in formulas (8) and (9), the transition amplitude A(f _*k ) of the cosine signal of the effective excitation frequency f _Tk and the environmental disturbance frequency f _Ik is calculated and transition phase θ(f _*k ), and according to the extracted transition amplitude A(f _*k ) and transition phase θ(f _*k ), construct the effective signal y _MT (n) and environmental disturbance shown in formula (10) Signal y _MI (n),

Wherein, W _*k is determined according to the matrix of the effective excitation frequency f _Tk or the environmental disturbance frequency f _Ik , and the preprocessed first vibration signal y _MHD (n) can be written as a column vector.

According to an embodiment of the present disclosure, determining the time-domain dynamic self-noise sequence and the frequency-domain dynamic self-noise power spectral density according to the first vibration signal, the effective signal, and the environmental interference signal may include the following operations:

The effective signal and the environmental interference signal are eliminated from the first vibration signal, and the time-domain dynamic self-noise sequence is obtained. According to the time-domain dynamic self-noise sequence and the total length of the signal, the frequency-domain dynamic self-noise power spectral density is determined.

In an exemplary embodiment, the pre-processed first vibration signal y MHD (n) is preferably used, and the pre-processed first vibration signal y _MHD (n) can be removed from the pre-processed first vibration signal y _MHD (n) with reference to formula (11). The signal y _MT (n) and the environmental interference signal y _MI (n), the reconstructed time-domain dynamic self-noise sequence p _MHD (n) is obtained, so that according to the time-domain dynamic self-noise sequence p _MHD (n) and the total signal The length, N, determines the frequency-domain dynamic self-noise power spectral density P _MHD (n).

p _MHD (n) = y _MHD (n) - y _MT (n) - y _MI (n) (11)

According to an embodiment of the present disclosure, determining the frequency-domain dynamic self-noise power spectral density according to the time-domain dynamic self-noise sequence and the total length of the signal may include the following operations:

According to the time-domain dynamic self-noise sequence, the second vibration signal and the third vibration signal, a new first amplitude squared coherence function and a new second amplitude squared coherence function are determined, wherein the new first amplitude squared coherence function is determined according to the time-domain dynamic self-noise sequence and the second vibration signal, and the new second amplitude square coherence function is determined according to the time-domain dynamic self-noise sequence and the third vibration signal output by the environmental vibration sensor;

Based on the first preset threshold and the second preset threshold, the new first amplitude squared coherence function and the new second amplitude squared coherence function are compared respectively to obtain a comparison result, wherein the comparison result represents the new first Whether there is a new valid signal in the amplitude squared coherence function, and/or whether there is a new environmental interference signal in the new second amplitude squared coherence function;

When the comparison result shows that there is no new effective signal and new environmental interference signal, according to the time-domain dynamic self-noise sequence and the total length of the signal, the frequency-domain dynamic self-noise power spectral density is determined;

When the comparison result indicates that there is at least one of a new effective signal and a new environmental interference signal, the time-domain dynamic self-noise sequence is determined as a new first vibration signal for utilizing the new first vibration signal A new first magnitude squared coherence function and a new second magnitude squared coherence function are computed.

预处理后的第一振动信号p_MHD(n)与预处理后的第三振动信号y_INF(n)之间的第二幅值平方相干函数

利用设定的第一预设阈值

和第二预设阈值

进行比较，得到对比结果，比较的目的在于判断p_MHD(n)是否仍包含有效信号成分和环境干扰成分。In an exemplary embodiment, a new first amplitude squared coherence function between the pre-processed first vibration signal p _MHD (n) and the pre-processed second vibration signal y _T (n) is calculated

The second amplitude squared coherence function between the pre-processed first vibration signal p _MHD (n) and the pre-processed third vibration signal y _INF (n)

Utilize the set first preset threshold

and the second preset threshold

The comparison is performed to obtain a comparison result, and the purpose of the comparison is to determine whether p _MHD (n) still contains effective signal components and environmental interference components.

According to an embodiment of the present disclosure, if the comparison result shows that the effective signal components and the environmental interference components are still included, the time-domain dynamic self-noise sequence p _MHD (n) is determined as the new first vibration signal y _MHD (n), for use in A new first amplitude squared coherence function and a new second amplitude squared coherence function are calculated using the new first vibration signal.

According to the embodiment of the present disclosure, if the comparison result shows that the effective signal component and the environmental interference component are not included, the frequency of the time-domain dynamic self-noise sequence p _MHD (n) of the measured MHD micro-angle vibration sensor is calculated according to formula (12). Domain dynamic self-noise power spectral density P _MHD (f), where the total signal length N.

According to the embodiment of the present disclosure, the above-mentioned time-domain dynamic self-noise sequence p _MHD (n) and frequency-domain dynamic self-noise power spectral density P _MHD (f) are the dynamic self-noise measurement results of the measured MHD micro-angle vibration sensor .

According to an embodiment of the present disclosure, the dynamic self-noise measurement method of the MHD micro-angle vibration sensor may further include the following operations:

Based on the bandwidth of the MHD micro-angle vibration sensor, a cosine signal of multiple different signal parameters is generated, wherein the signal parameters may include at least one of the following: amplitude, frequency and phase;

Based on the sampling frequency of the cosine signal, a plurality of initial mixing excitation signal sequences are generated according to the plurality of cosine signals;

Based on a preset range, a target mixing excitation signal sequence is determined from a plurality of initial mixing excitation signal sequences according to the crest factor of each initial mixing excitation signal sequence, wherein the crest factor is a signal according to the initial mixing excitation signal sequence Peak and power determined.

According to the embodiment of the present disclosure, the crest factor can be determined by the ratio of the signal peak value and the power. In the embodiment of the present disclosure, an initial mixing excitation signal sequence with a crest factor of not more than 3 is preferably used.

According to an embodiment of the present disclosure, the generation of the target mixing excitation signal sequence Ω(n) refers to formula (13).

Among them, n is the serial number of the target mixing _excitation signal sequence, n _{= 1} , . , frequency and phase, k=1,...,K, K is the number of cosine signals; F _s is the sampling frequency.

FIG. 3 schematically shows a result diagram A of the coherence coefficient according to an embodiment of the present disclosure. FIG. 4 schematically shows a schematic diagram B of results of coherence coefficients according to an embodiment of the present disclosure. FIG. 5 schematically shows a schematic diagram of the results of the time-domain dynamic self-noise sequence and the frequency-domain dynamic self-noise power spectral density according to an embodiment of the present disclosure.

其计算得到的结果如图3所示，基于第一预设阈值

对其进行筛选，从而得到有效激励频率。In an exemplary embodiment, the target mixing excitation signal sequence Ω(n) used produces effective frequencies of 10 Hz, 20 Hz, 30 Hz, 40 Hz, 60 Hz, 80 Hz, 100 Hz. The first amplitude square coherence function determined according to the preprocessed first vibration signal y _MHD (n) and the preprocessed second vibration signal y _T (n)

The calculated result is shown in Figure 3, based on the first preset threshold

Screen it to get the effective excitation frequency.

其计算得到的结果如图3所示，基于第二预设阈值

对其进行筛选，以得到环境干扰频率。经过本公开的方法，得到的时域动态自噪声序列p_MHD(n)，分别计算其与预处理后的第二振动信号y_T(n)、预处理后的第三振动信号y_INF(n)之间新的第一幅值平方相干函数

和新的第二幅值平方相干函数

其计算得到的结果如图4所示，由图4可知，利用第一预设阈值

和第二预设阈值

判断时域动态自噪声序列p_MHD(n)已不包含有效信号成分和环境干扰成分，此时可以根据时域动态自噪声序列p_MHD(n)确定被测的MHD微角振动传感器的频域动态自噪声功率谱密度P_MHD(n)，其中，时域动态自噪声序列p_MHD(n)和频域动态自噪声功率谱密度P_MHiD(n)如图5所示。The environmental vibration interference frequency in the test can be determined according to the second amplitude square coherence function of the preprocessed first vibration signal y _MHD (n) and the preprocessed third vibration signal y _INF (n).

The calculated result is shown in Figure 3, based on the second preset threshold

It is screened for environmental disturbance frequencies. Through the method of the present disclosure, the obtained time-domain dynamic self-noise sequence p _MHD (n) is calculated separately from the pre-processed second vibration signal y _T (n) and the pre-processed third vibration signal y _INF (n ) between the new first magnitude squared coherence function

and the new second magnitude squared coherence function

The calculated result is shown in Figure 4. It can be seen from Figure 4 that the first preset threshold is used.

and the second preset threshold

It is judged that the time-domain dynamic self-noise sequence p _MHD (n) does not contain effective signal components and environmental interference components. At this time, the frequency domain of the measured MHD micro-angle vibration sensor can be determined according to the time-domain dynamic self-noise sequence p _MHD (n). The dynamic self-noise power spectral density P _MHD (n), where the time-domain dynamic self-noise sequence p _MHD (n) and the frequency-domain dynamic self-noise power spectral density P _MHiD (n) are shown in Figure 5.

6 schematically shows a block diagram of a dynamic self-noise measurement system of an MHD micro-angle vibration sensor according to an embodiment of the present disclosure.

As shown in FIG. 6 , the dynamic self-noise measurement system 600 of the MHD micro-angle vibration sensor may include a signal conversion module 601 , a controller 602 , an angular vibration table 603 , an MHD micro-angle vibration sensor 604 , an environmental vibration sensor 605 and a calculation module 606 .

The signal conversion module 601 is used for converting the received target mixed frequency excitation signal sequence into an excitation analog signal.

The controller 602 is configured to receive the excitation simulation signal sequence, and control the angular vibration table 603 to vibrate in response to the excitation simulation signal sequence.

The angular vibrating table 603 is used to vibrate under the control of the controller 602 and output a second vibrating signal in response to the vibration.

The MHD micro-angular vibration sensor 604 is coaxially fixed to the table surface of the angular vibration table 603, and is used to vibrate synchronously when the angular vibration table 603 vibrates, and outputs a first vibration signal in response to the vibration.

The environmental vibration sensor 605 is fixedly connected to the base of the angular vibration table 603, and is used for synchronously vibrating when the angular vibration table 603 vibrates, and outputs a third vibration signal in response to the vibration.

The calculation module 606 is configured to determine the time-domain dynamic self-noise sequence and the frequency-domain dynamic self-noise power spectral density of the MHD micro-angle vibration sensor 604 according to the first vibration signal, the second vibration signal and the third vibration signal.

According to an embodiment of the present disclosure, the time domain of the MHD micro-angle vibration sensor 604 is calculated by using the first vibration signal of the MHD micro-angle vibration sensor 604, combining the second vibration signal of the angular vibration and the third vibration signal of the environmental vibration sensor 605 The dynamic self-noise sequence and the frequency-domain dynamic self-noise power spectral density avoid the problem of large error in the test results caused by the introduction of other auxiliary MHD micro-angle vibration sensors 604 and the use of prior knowledge, and improve the dynamic performance of the MHD micro-angle vibration sensor 604 Measurement accuracy of self-noise. At the same time, the measurement system of the present disclosure has a simple structure and is not easy to generate structural resonance, so that the measurement error is small and the test accuracy is high; the effect of suppressing unknown vibration in the external environment is good; the measurement frequency range is large, and it can cover the MHD micro-angle vibration. The operating bandwidth of the sensor 604 .

According to an embodiment of the present disclosure, the calculation module 606 may include a calculation sub-module, a construction sub-module, and a determination sub-module.

The calculation submodule is used to calculate the first amplitude squared coherence function and the second amplitude squared coherence function according to the first vibration signal, the second vibration signal and the third vibration signal, wherein the first amplitude squared coherence function is based on The first vibration signal and the second vibration signal are determined, and the second amplitude square coherence function is determined according to the first vibration signal and the third vibration signal output by the environmental vibration sensor 605 .

A construction sub-module is used to construct an effective signal and an environmental interference signal respectively according to the effective excitation frequency in the first amplitude squared coherence function and the environmental interference frequency in the second amplitude squared coherence function.

The determination submodule is used for determining the time-domain dynamic self-noise sequence and the frequency-domain dynamic self-noise power spectral density according to the first vibration signal, the effective signal and the environmental interference signal.

According to an embodiment of the present disclosure, the computing module 606 may also include a preprocessing sub-module.

The preprocessing submodule is used to remove the DC bias signal in the first vibration signal, the second vibration signal and the third vibration signal respectively, and obtain the preprocessed first vibration signal, the preprocessed second vibration signal and the preprocessed vibration signal. The processed third vibration signal.

According to an embodiment of the present disclosure, the calculation sub-module may include a first determination unit and a second determination unit.

The first determination unit is used to determine the first transition function corresponding to the signal and the Second transition function.

The second determining unit is configured to determine, according to the first transition function, the second transition function and the third transition function corresponding to the preprocessed first vibration signal, the first amplitude squared coherence function or the second amplitude squared coherence function corresponding to the signal Value squared coherence function.

According to an embodiment of the present disclosure, the construction submodule may include a screening unit, a third determination unit, a first construction unit, and a second construction unit.

A screening unit, configured to screen out the first amplitude squared coherence function and the second amplitude squared coherence function based on the first preset threshold and the second preset threshold, respectively, to obtain an effective excitation corresponding to the first amplitude squared coherence function frequency and ambient interference frequency of the second magnitude squared coherence function.

The third determining unit is configured to, for any one of the first amplitude squared coherence function and the second amplitude squared coherence function, determine the transition amplitude and transition phase according to the first vibration signal and the intermediate function value, wherein the intermediate The function value is determined according to the effective excitation frequency or environmental disturbance frequency corresponding to the coherence function.

The first construction unit is configured to construct an effective signal according to the transition amplitude and transition phase corresponding to the first amplitude square coherence function.

The second construction unit is configured to construct the environmental interference signal according to the transition amplitude and transition phase corresponding to the second amplitude squared coherence function.

According to an embodiment of the present disclosure, the determination submodule may include a culling unit and a fourth determination unit.

The elimination unit is used for eliminating the effective signal and the environmental interference signal from the first vibration signal to obtain the time-domain dynamic self-noise sequence.

The fourth determining unit is configured to determine the power spectral density of the dynamic self-noise in the frequency domain according to the dynamic self-noise sequence in the time domain and the total length of the signal.

According to an embodiment of the present disclosure, the fourth determination unit may include a first determination subunit, a comparison subunit, a second determination subunit, and a third determination subunit.

The first determination subunit is configured to determine a new first amplitude squared coherence function and a new second amplitude squared coherence function according to the time-domain dynamic self-noise sequence, the second vibration signal and the third vibration signal, wherein the new The first amplitude squared coherence function is determined according to the time domain dynamic self-noise sequence and the second vibration signal, and the new second amplitude squared coherence function is based on the time domain dynamic self-noise sequence and the third output of the environmental vibration sensor 605. Vibration signal determined.

a comparison subunit, configured to compare the new first amplitude squared coherence function and the new second amplitude squared coherence function based on the first preset threshold and the second preset threshold, respectively, to obtain a comparison result, wherein the comparison The result indicates whether there is a new valid signal in the new first amplitude squared coherence function, and/or whether there is a new environmental interference signal in the new second amplitude squared coherence function.

The second determination subunit is used to determine the frequency-domain dynamic self-noise power spectral density according to the time-domain dynamic self-noise sequence and the total signal length when the comparison result indicates that there are no new valid signals and new environmental interference signals.

The third determination subunit is configured to determine the time-domain dynamic self-noise sequence as a new first vibration signal when the comparison result indicates that at least one of a new effective signal and a new environmental interference signal exists, so as to use for calculating a new first amplitude squared coherence function and a new second amplitude squared coherence function using the new first vibration signal.

According to an embodiment of the present disclosure, the dynamic self-noise measurement system of the MHD micro-angle vibration sensor 604 may further include an industrial computer 607 .

The industrial computer 607 is used to perform the following operations:

Based on the bandwidth of the MHD micro-angle vibration sensor 604, a cosine signal of a plurality of different signal parameters is generated, wherein the signal parameters may include at least one of the following: amplitude, frequency and phase;

Based on the sampling frequency of the cosine signal, a plurality of initial mixing excitation signal sequences are generated according to the plurality of cosine signals;

Based on a preset range, a target mixing excitation signal sequence is determined from a plurality of initial mixing excitation signal sequences according to the crest factor of each initial mixing excitation signal sequence, wherein the crest factor is a signal according to the initial mixing excitation signal sequence Peak and power determined.

It should be noted that the method executed by the computing module 606 may be processed by an industrial computer, or the computing module 606 may be integrated in the industrial computer.

Any of the modules, sub-modules, units, sub-units, or at least part of the functions of any of them according to embodiments of the present disclosure may be implemented in one module. Any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure may be divided into multiple modules for implementation. Any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure may be implemented at least partially as hardware circuits, such as Field Programmable Gate Array (FPGA), programmable logic Arrays (Programmable Logic Arrays, PLA), system-on-chip, system-on-substrate, system-on-package, Application-Specific Integrated Circuit (ASIC), or any other reasonable means of hardware or Firmware, or any one of software, hardware and firmware, or any appropriate combination of any of them. Alternatively, one or more of the modules, sub-modules, units, and sub-units according to embodiments of the present disclosure may be implemented at least in part as computer program modules that, when executed, may perform corresponding functions.

It should be noted that the part of the dynamic self-noise measurement system of the MHD micro-angle vibration sensor in the embodiment of the present disclosure corresponds to the part of the dynamic self-noise measurement method of the MHD micro-angle vibration sensor in the embodiment of the present disclosure. For the description of the dynamic self-noise measurement system part of the vibration sensor, please refer to the part of the dynamic self-noise measurement method of the MHD micro-angle vibration sensor, which will not be repeated here.

Figure 7 schematically shows a block diagram of an electronic device suitable for implementing the method described above, according to an embodiment of the present disclosure. The electronic device shown in FIG. 7 is only an example, and should not impose any limitation on the function and scope of use of the embodiments of the present disclosure.

It should be noted that the electronic device 700 of the present disclosure can be used to implement the function of the computing module 606, and the electronic device 700 is respectively connected to the angular vibration table, the environmental vibration sensor and the MHD micro-angular vibration sensor through the signal acquisition module to collect the angle Signals from shaker, ambient vibration sensor, and MHD micro-angle vibration sensor.

The electronic device of the present disclosure can also be used to realize the function of an industrial computer. In this case, the electronic device also needs to be connected in communication with the signal conversion module.

As shown in FIG. 7 , an electronic device 700 according to an embodiment of the present disclosure includes a processor 701 that can be loaded into a random access memory according to a program stored in a read-only memory (Read-Only Memory, ROM) 702 or from a storage part 708 Various appropriate operations and processes are executed by the program in the (Random Access Memory, RAM) 703 . The processor 701 may include, for example, a general-purpose microprocessor (eg, a CPU), an instruction set processor and/or a related chipset, and/or a special-purpose microprocessor (eg, an application specific integrated circuit (ASIC)), among others. The processor 701 may also include on-board memory for caching purposes. The processor 701 may include a single processing unit or multiple processing units for performing different actions of the method flow according to the embodiments of the present disclosure.

In the RAM 703, various programs and data necessary for the operation of the electronic device 700 are stored. The processor 701 , the ROM 702 and the RAM 703 are connected to each other through a bus 704 . The processor 701 performs various operations of the method flow according to the embodiment of the present disclosure by executing the programs in the ROM 702 and/or the RAM 703 . Note that the program may also be stored in one or more memories other than the ROM 702 and the RAM 703 . The processor 701 may also perform various operations of the method flow according to the embodiments of the present disclosure by executing programs stored in the one or more memories.

According to an embodiment of the present disclosure, the electronic device 700 may also include an input/output (I/O) interface 705 that is also connected to the bus 704 . The system 700 may also include one or more of the following components connected to the I/O interface 705: an input portion 706 including a keyboard, mouse, etc.; including components such as a cathode ray tube (CRT), a Liquid Crystal Display (LCD) ), etc., and an output section 707 of speakers, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN card, a modem, and the like. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I/O interface 705 as needed. A removable medium 711, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is mounted on the drive 710 as needed so that a computer program read therefrom is installed into the storage section 708 as needed.

According to an embodiment of the present disclosure, the method flow involved in the computing module according to the embodiment of the present disclosure can be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the method illustrated in the flowchart. In such an embodiment, the computer program may be downloaded and installed from the network via the communication portion 709 and/or installed from the removable medium 711 . When the computer program is executed by the processor 701, the above-described functions defined in the system of the embodiment of the present disclosure are performed. According to embodiments of the present disclosure, the systems, devices, systems, modules, units, etc. described above may be implemented by computer program modules.

The present disclosure also provides a computer-readable storage medium. The computer-readable storage medium may be included in the device/system/system described in the above embodiments; it may also exist alone without being assembled into the device/system/system. system/system. The above-mentioned computer-readable storage medium carries one or more programs, and when the above-mentioned one or more programs are executed, implement the method according to the embodiment of the present disclosure.

According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it may include but not limited to: portable computer disk, hard disk, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM (Erasable Programmable Read Only Memory, EPROM) or flash memory), Portable compact disk read-only memory (Computer Disc Read-Only Memory, CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above. In this disclosure, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, system, or device.

For example, according to embodiments of the present disclosure, a computer-readable storage medium may include one or more memories other than ROM 702 and/or RAM 703 and/or ROM 702 and RAM 703 described above.

Embodiments of the present disclosure also include a computer program product, which includes a computer program, the computer program includes program codes for executing the methods provided by the embodiments of the present disclosure, and when the computer program product runs on an electronic device, the program The code is used to enable the electronic device to implement the dynamic self-noise measurement method of the MHD micro-angle vibration sensor provided by the embodiment of the present disclosure.

When the computer program is executed by the processor 701, the above-mentioned functions defined in the system/system of the embodiment of the present disclosure are performed. According to embodiments of the present disclosure, the systems, systems, modules, units, etc. described above may be implemented by computer program modules.

In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device, a magnetic storage device, or the like. In another embodiment, the computer program may also be transmitted, distributed in the form of a signal over a network medium, and downloaded and installed through the communication section 709, and/or installed from a removable medium 711. The program code embodied by the computer program may be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.

According to the embodiments of the present disclosure, the program code for executing the computer program provided by the embodiments of the present disclosure may be written in any combination of one or more programming languages, and specifically, high-level procedures and/or object-oriented programming may be used. programming language, and/or assembly/machine language to implement these computational programs. Programming languages include, but are not limited to, languages such as Java, C++, python, "C" or similar programming languages. The program code may execute entirely on the user computing device, partly on the user device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (eg, using an Internet service provider business via an Internet connection).

The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code that contains one or more logical functions for implementing the specified functions executable instructions. It should also be noted that, in some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It is also noted that each block of the block diagrams or flowchart illustrations, and combinations of blocks in the block diagrams or flowchart illustrations, can be implemented in special purpose hardware-based systems that perform the specified functions or operations, or can be implemented using A combination of dedicated hardware and computer instructions is implemented. Those skilled in the art will appreciate that various combinations and/or combinations of features recited in various embodiments and/or claims of the present disclosure are possible, even if such combinations or combinations are not expressly recited in the present disclosure. In particular, various combinations and/or combinations of the features recited in the various embodiments of the present disclosure and/or in the claims may be made without departing from the spirit and teachings of the present disclosure. All such combinations and/or combinations fall within the scope of this disclosure.

Embodiments of the present disclosure have been described above. However, these examples are for illustrative purposes only, and are not intended to limit the scope of the present disclosure. Although the various embodiments are described above separately, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. The scope of the present disclosure is defined by the appended claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art can make various substitutions and modifications, and these substitutions and modifications should all fall within the scope of the present disclosure.

Claims (10)

1. A dynamic self-noise measurement method of an MHD micro-angle vibration sensor, comprising: Utilize the controller to receive the excitation analog signal sequence, wherein the excitation analog signal is obtained by converting the target mixing excitation signal sequence by using the signal conversion module; In response to the excitation simulation signal sequence, the controller controls the angular shaking table to vibrate, so that the environmental vibration sensor fixed to the angular shaking table and the MHD micro-axis fixed to the angular shaking table coaxially. The angular vibration sensor vibrates synchronously; In response to the vibration, the MHD micro-angular vibration sensor generates a first vibration signal, the angular vibration table generates a second vibration signal, and the ambient vibration sensor generates a third vibration signal; According to the first vibration signal, the second vibration signal and the third vibration signal, the time-domain dynamic self-noise sequence and the frequency-domain dynamic self-noise power spectral density of the MHD micro-angle vibration sensor are determined. 2. The method according to claim 1, wherein the time domain dynamic self-determination of the MHD micro-angle vibration sensor is determined according to the first vibration signal, the second vibration signal and the third vibration signal. Noise sequence and frequency-domain dynamic self-noise power spectral density, including: Calculate a first amplitude squared coherence function and a second amplitude squared coherence function according to the first vibration signal, the second vibration signal and the third vibration signal, wherein the first amplitude squared coherence function is determined according to the first vibration signal and the second vibration signal, and the second amplitude square coherence function is determined according to the first vibration signal and the third vibration signal output by the environmental vibration sensor; According to the effective excitation frequency in the first amplitude squared coherence function and the environmental interference frequency in the second amplitude squared coherence function, construct the effective signal and the environmental interference signal respectively; The time-domain dynamic self-noise sequence and the frequency-domain dynamic self-noise power spectral density are determined according to the first vibration signal, the effective signal and the environmental interference signal. 3. The method of claim 2, wherein before calculating the first magnitude squared coherence function and the second magnitude squared coherence function, further comprising: Respectively remove the DC bias signal in the first vibration signal, the second vibration signal and the third vibration signal to obtain the preprocessed first vibration signal, the preprocessed second vibration signal and the preprocessed After the third vibration signal. 4. The method according to claim 3, wherein the first amplitude square coherence function and the first amplitude square coherence function are calculated according to the first vibration signal, the second vibration signal and the third vibration signal output by the environmental vibration sensor. Two magnitude squared coherence functions, including: For any one of the second vibration signal and the third vibration signal, according to the signal, the total length of the signal, and the preprocessed first vibration signal, determine the first vibration signal corresponding to the signal a transition function and a second transition function; According to the first transition function, the second transition function and the third transition function corresponding to the preprocessed first vibration signal, determine the first amplitude squared coherence function corresponding to the signal or the second magnitude squared coherence function. 5. The method according to claim 2, wherein the effective signal is constructed respectively according to the effective excitation frequency in the first amplitude squared coherence function and the environmental interference frequency in the second amplitude squared coherence function and environmental interference signals, including: Based on the first preset threshold and the second preset threshold, respectively, the first amplitude squared coherence function and the second amplitude squared coherence function are screened to obtain all the first amplitude squared coherence functions corresponding to the first amplitude squared coherence function. the effective excitation frequency and the environmental interference frequency of the second amplitude squared coherence function; For any one of the first amplitude squared coherence function and the second amplitude squared coherence function, a transition amplitude and transition phase are determined according to the first vibration signal and the intermediate function value, wherein the intermediate function the value is determined according to the effective excitation frequency or the environmental disturbance frequency corresponding to the coherence function; constructing the effective signal according to the transition amplitude and the transition phase corresponding to the first amplitude squared coherence function; The ambient interference signal is constructed from the transition amplitude and the transition phase corresponding to the second amplitude squared coherence function. 6. The method according to claim 5, wherein the time domain dynamic self-noise sequence and the frequency domain dynamic self-noise power spectral density are determined according to the first vibration signal, the effective signal and the environmental interference signal ,include: Eliminate the effective signal and the environmental interference signal from the first vibration signal to obtain the time-domain dynamic self-noise sequence; The frequency-domain dynamic self-noise power spectral density is determined according to the time-domain dynamic self-noise sequence and the total length of the signal. 7. The method according to claim 6, wherein the determining the frequency-domain dynamic self-noise power spectral density according to the time-domain dynamic self-noise sequence and the total length of the signal comprises: According to the time-domain dynamic self-noise sequence, the second vibration signal and the third vibration signal, a new first amplitude squared coherence function and a new second amplitude squared coherence function are determined, wherein the new first amplitude squared coherence function An amplitude squared coherence function is determined according to the time-domain dynamic self-noise sequence and the second vibration signal, and the new second amplitude squared coherence function is determined according to the time-domain dynamic self-noise sequence and ambient vibration Determined by the third vibration signal output by the sensor; Based on the first preset threshold and the second preset threshold, the new first amplitude squared coherence function and the new second amplitude squared coherence function are respectively compared to obtain a comparison result, wherein the The comparison result represents whether there is a new valid signal in the new first amplitude squared coherence function, and/or whether there is a new environmental interference signal in the new second amplitude squared coherence function; When the comparison result indicates that the new effective signal and the new environmental interference signal do not exist, determine the frequency-domain dynamic self-noise according to the time-domain dynamic self-noise sequence and the total length of the signal Power Spectral Density; In the case that the comparison result indicates that at least one of the new effective signal and the new environmental interference signal exists, the time-domain dynamic self-noise sequence is determined as a new first vibration signal, so as to use for calculating a new first amplitude squared coherence function and a new second amplitude squared coherence function using the new first vibration signal. 8. The method of claim 1, further comprising: Based on the bandwidth of the MHD micro-angle vibration sensor, a cosine signal of a plurality of different signal parameters is generated, wherein the signal parameters include at least one of the following: amplitude, frequency and phase; Based on the sampling frequency of the cosine signal, generate a plurality of initial mixing excitation signal sequences according to the plurality of cosine signals; Based on a preset range, the target frequency mixing excitation signal sequence is determined from a plurality of the initial frequency mixing excitation signal sequences according to the crest factor of each of the initial frequency mixing excitation signal sequences, wherein the crest factor is based on The signal peak value and power of the initial mixing excitation signal sequence are determined. 9. A dynamic self-noise measurement system of an MHD micro-angle vibration sensor, comprising: The signal conversion module is used to convert the received target mixing excitation signal sequence into excitation analog signal; a controller, configured to receive the excitation analog signal sequence, and control the angular vibration table to vibrate in response to the excitation analog signal sequence; The angular vibration table is used to vibrate under the control of the controller, and output a second vibration signal in response to the vibration; The MHD micro-angle vibration sensor is coaxially fixed with the table surface of the angular vibration table, and is used to vibrate synchronously when the angular vibration table vibrates, and in response to the vibration, output a first vibration signal ; an environmental vibration sensor, fixed to the base of the angular vibration table, for synchronously vibrating when the angular vibration table vibrates, and outputting a third vibration signal in response to the vibration; A calculation module for determining the time-domain dynamic self-noise sequence and the frequency-domain dynamic self-noise power spectrum of the MHD micro-angle vibration sensor according to the first vibration signal, the second vibration signal and the third vibration signal density. 10. The measurement system of claim 9, further comprising: Industrial computer, which is used to perform the following operations: Based on the bandwidth of the MHD micro-angle vibration sensor, a cosine signal of a plurality of different signal parameters is generated, wherein the signal parameters include at least one of the following: amplitude, frequency and phase; Based on the sampling frequency of the cosine signal, generate a plurality of initial mixing excitation signal sequences according to the plurality of cosine signals; Based on a preset range, the target frequency mixing excitation signal sequence is determined from a plurality of the initial frequency mixing excitation signal sequences according to the crest factor of each of the initial frequency mixing excitation signal sequences, wherein the crest factor is based on The signal peak value and power of the initial mixing excitation signal sequence are determined.

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