CN112269196B - Rubidium clock abnormity diagnosis method based on time-frequency characteristics - Google Patents

Rubidium clock abnormity diagnosis method based on time-frequency characteristics Download PDF

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CN112269196B
CN112269196B CN202011100802.1A CN202011100802A CN112269196B CN 112269196 B CN112269196 B CN 112269196B CN 202011100802 A CN202011100802 A CN 202011100802A CN 112269196 B CN112269196 B CN 112269196B
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rubidium clock
characteristic value
value
time
frequency
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周建华
刘勇
赵金贤
孙健
冯炜
韦官余
闫芳君
李跃跃
罗凯
杨浩
徐欢
樊焕贞
薛润民
房红征
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People's Liberation Army 61081 Unit
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/24—Acquisition or tracking or demodulation of signals transmitted by the system
    • G01S19/25—Acquisition or tracking or demodulation of signals transmitted by the system involving aiding data received from a cooperating element, e.g. assisted GPS
    • G01S19/256—Acquisition or tracking or demodulation of signals transmitted by the system involving aiding data received from a cooperating element, e.g. assisted GPS relating to timing, e.g. time of week, code phase, timing offset
    • G—PHYSICS
    • G04—HOROLOGY
    • G04F—TIME-INTERVAL MEASURING
    • G04F5/00—Apparatus for producing preselected time intervals for use as timing standards
    • G04F5/14—Apparatus for producing preselected time intervals for use as timing standards using atomic clocks

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Abstract

The invention provides a rubidium clock abnormity diagnosis method based on time-frequency characteristics, which is used for solving the problem that in the prior art, the rubidium clock working state abnormity is diagnosed through telemetering data. The rubidium clock abnormality diagnosis method comprises the following steps: step S1, extracting typical characteristic values of the telemetering rubidium clock signal in a time domain and a frequency domain; step S2, analyzing the variation trend of the typical characteristic values extracted in the period; step S3, determining a threshold range of the characteristic value according to the time-frequency characteristic value under the normal condition; and step S4, analyzing the variation trend of the time domain characteristic value and the frequency domain characteristic value within the characteristic value threshold range, and analyzing whether the rubidium clock is abnormal or not according to the variation trend. The method provided by the invention has the advantages that the rubidium clock abnormity diagnosis is realized based on time domain and frequency domain characteristic analysis, the rubidium clock abnormity is accurately detected and identified, the on-satellite rubidium clock working state is intelligently evaluated, the data support is provided for the ground control center decision, and the long-term management capability of the on-orbit navigation satellite effective load key component is improved.

Description

Rubidium clock abnormity diagnosis method based on time-frequency characteristics
Technical Field
The invention belongs to the field of satellite navigation, and particularly relates to a rubidium clock abnormity diagnosis method based on time-frequency characteristics.
Background
The rubidium atomic clock has the characteristics of small volume, small mass, small power consumption, low price and the like, is widely applied to the time keeping and time service of a spacecraft, is a precise clock source of a Beidou navigation satellite payload, and has important influence on the navigation positioning precision due to the stability. In a Beidou navigation satellite system, a satellite-borne rubidium clock is used as an on-satellite time reference for navigation signal generation and system ranging, an accurate and stable frequency source is provided for a navigation system, the on-satellite time reference is a core component of a navigation satellite payload, and the performance and the working state of the on-satellite time reference directly determine the navigation positioning accuracy of a user. Therefore, it is necessary to ensure stable operation of the rubidium clock, predict possible faults, and perform timely redundancy switching according to fault signs, thereby ensuring continuous and stable operation of the system.
In the prior art, rubidium clock abnormity is monitored by analyzing telemetering data in real time. However, the data volume of the satellite telemetry parameters is extremely large, and the effect is poor by adopting a conventional data processing method; meanwhile, the telemetering parameters related to the on-satellite rubidium clock mostly change smoothly, so that failure foreboding information is difficult to observe directly from raw data, and higher requirements are provided for abnormality diagnosis.
Disclosure of Invention
In view of the above-mentioned drawbacks and deficiencies of the prior art, the present invention provides a rubidium clock abnormality diagnosis method based on time-frequency characteristics, wherein a trend analysis is performed on a typical characteristic value of an extracted telemetered rubidium clock signal in a time domain and a frequency domain through statistical normal time-frequency characteristic information in each cycle time, so as to detect an operating condition of a rubidium clock and accurately detect and identify rubidium clock abnormality.
In order to achieve the above purpose, the embodiment of the invention adopts the following technical scheme:
the embodiment of the invention provides a rubidium clock abnormality diagnosis method based on time-frequency characteristics, which comprises the following steps:
step S1, extracting typical characteristic values of the telemetering rubidium clock signal in a time domain and a frequency domain;
step S2, analyzing the variation trend of the typical characteristic values extracted in the period;
step S3, determining a threshold range of the characteristic value according to the time-frequency characteristic value under the normal condition;
and step S4, analyzing the variation trend of the time domain characteristic value and the frequency domain characteristic value within the characteristic value threshold range, and analyzing whether the rubidium clock is abnormal or not according to the variation trend.
In the above scheme, the telemetered rubidium clock signal is a signal within a cycle, and the extracted characteristic value is a time-frequency characteristic value of the signal within the cycle.
In the above scheme, the typical characteristic value of the time domain adopts a mean value M, a standard deviation S and an extreme value P in a fixed time window, and the calculation formula is as follows:
Figure BDA0002725270200000021
Figure BDA0002725270200000022
Figure BDA0002725270200000023
in the formulas (1) to (3), N is the number of sampling points in a fixed time window, aiFor the value of the ith remote measurement point, M, S and P are the mean, standard deviation and extreme value of the remote measurement value in the fixed time window, respectively.
In the above scheme, the typical characteristic value of the frequency domain, which uses the frequency spectrum x (k) and the power spectrum p (w), is calculated as follows:
Figure BDA0002725270200000024
Figure BDA0002725270200000025
in the formulas (4) and (5), N is the number of sampling points in a fixed time window, aiThe value of the ith remote measuring point is T, and the length of the fixed time window is T; fT(w) is a Fourier transform of the telemetric rubidium clock signal.
In the above aspect, the fixed time window is one cycle of a telemetric rubidium clock signal.
In the foregoing scheme, the step S4 further includes:
step S41, when the change of the characteristic value is within the threshold value range, determining that the rubidium clock is normal;
step S42, when the change of the characteristic value exceeds the statistical threshold range and keeps increasing, determining that the rubidium clock has a fault;
step S43, when the change of the characteristic value exceeds the statistical threshold range and falls back to the normal interval within the set time, determining that the rubidium clock is disturbed by noise to generate transient abnormal disturbance;
in step S44, when the variation of the characteristic value exceeds the statistical threshold range and remains stable for a long time, it is determined that the performance of the rubidium clock is abnormal.
The invention has the following beneficial effects:
according to the rubidium clock abnormality diagnosis method based on the time-frequency characteristics, the time-domain and frequency-domain typical characteristics of the telemetered rubidium clock signals are extracted, meanwhile, the threshold interval of the time-frequency characteristics under the normal condition is counted, the change trend of the extracted time-frequency characteristic values is analyzed on the basis of the threshold interval, and the rubidium clock abnormality detection and identification are achieved based on the results of time-domain and frequency-domain characteristic analysis, so that the telemetered rubidium clock abnormality is accurately detected and identified, the working state of a rubidium clock on a satellite is intelligently evaluated, data support is provided for a ground control center decision, and the long-term management capability of the rubidium clock abnormality diagnosis method on the key components of the effective load of an on-orbit navigation satellite is improved. The method for analyzing the time window of the streaming data is adopted, various characteristic values (including time domain, frequency domain and the like) of the rubidium clock signal in each time period are accurately identified, sensitive key characteristics representing rubidium clock abnormality are summarized and extracted, and accurate detection of the rubidium clock signal abnormality of the navigation satellite is successfully achieved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a flowchart of a rubidium clock abnormality diagnosis method based on time-frequency characteristics according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating the variation of time-frequency characteristics when the telemetric rubidium clock is correct according to the embodiment of the present invention;
FIG. 3 is a diagram illustrating the variation of time-frequency characteristics of a rubidium telemetering clock when a fault occurs according to an embodiment of the present invention;
FIG. 4 is a schematic diagram illustrating changes in time-frequency characteristics of a telemetered rubidium clock when disturbed by noise to generate transient abnormal disturbance according to an embodiment of the present invention;
fig. 5 is a diagram illustrating changes in time-frequency characteristics when performance of a telemetered rubidium clock is abnormal according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict. The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings.
According to the method for detecting and identifying the rubidium clock abnormality based on the time-frequency characteristic analysis, provided by the embodiment of the invention, the rubidium clock abnormality is detected and identified by extracting the time domain and frequency domain typical characteristics of a telemetering rubidium clock signal and based on the results of the time domain and frequency domain characteristic analysis. When the method is used for detecting and identifying the telemetering rubidium clock abnormality, firstly, typical characteristic values of a telemetering rubidium clock signal in a time domain and a frequency domain are extracted; then analyzing the change trend of the characteristic value based on the time-frequency characteristic information counted under the normal distribution condition; and finally, detecting and identifying telemetering rubidium clock signal abnormality according to the analysis result. When the change of the characteristic value exceeds the statistical threshold value and keeps increasing, the telemetering rubidium clock is considered to be out of order; when the change of the characteristic value exceeds the range of the statistical threshold value and falls back to a normal interval within set time, the telemetering rubidium clock is considered to be subjected to noise interference to generate transient abnormal disturbance; and when the change of the characteristic value exceeds the statistical threshold range and is kept stable for a long time, judging that the performance of the telemetric rubidium clock is abnormal. According to the method, the detection and identification of the telemetering rubidium clock abnormality are realized through the analysis of the time domain and frequency domain characteristics of the telemetering rubidium clock signal in each cycle time, the telemetering rubidium clock abnormality can be accurately detected and identified, and the method has a better processing effect.
Fig. 1 is a flowchart illustrating a rubidium clock abnormality diagnosis method based on time-frequency characteristics according to an embodiment of the present invention. As shown in fig. 1, the method for diagnosing an abnormality of a telemetric rubidium clock includes the steps of:
and step S1, extracting typical characteristic values of the telemetered rubidium clock signal in a time domain and a frequency domain.
In this step, the telemetered rubidium clock signal is a signal within a period, and the extracted characteristic value is a time-frequency characteristic value of the signal within the period.
As mentioned above, the typical feature value of the time domain, which uses the mean value M, the standard deviation S and the extreme value P in the fixed time window, is calculated as follows:
Figure BDA0002725270200000041
Figure BDA0002725270200000042
Figure BDA0002725270200000051
in the formulas (1) to (3), N is the number of sampling points in a fixed time window, aiFor the telemetered rubidium clock signal at the ith remote measurement point, M, S and P are the mean, standard deviation and extremum of the remote measurements over a fixed time window, respectively.
Preferably, the fixed time window is one cycle of a telemetered rubidium clock signal.
For typical eigenvalues of the frequency domain, using the frequency spectrum x (k) and the power spectrum p (w), the calculation formula is as follows:
Figure BDA0002725270200000052
Figure BDA0002725270200000053
in the formulae (4) and (5), X (k) is a frequency spectrum; p (w) is a power spectrum; t isThe length or period of the fixed time window; fT(w) is a Fourier transform of the telemetric rubidium clock signal.
In step S2, the variation trend of the characteristic feature values extracted in the cycle is analyzed.
The method comprises the following steps of preprocessing a typical characteristic value, extracting the characteristic value of a sampling point in a fixed time window, and analyzing the change trend of a time domain characteristic value and a frequency domain characteristic value.
And step S3, determining a threshold range of the characteristic value according to the time-frequency characteristic value under the normal condition.
Table 1 lists examples of threshold ranges of time domain feature values counted under normal conditions within a certain fixed time window; table 2 lists examples of threshold ranges of frequency domain eigenvalue spectra counted under normal conditions within a certain fixed time window; table 3 lists examples of threshold ranges of the frequency domain eigenvalue power spectrum within a certain fixed time window under normal conditions. As shown in table 1, the threshold range is a range between a lower limit and an upper limit; as shown in tables 2 to 3, the threshold range is within a predetermined proportion of the reference amplitude value, for example, within ± 30%.
TABLE 1
Time domain feature identification Lower limit of statistical threshold Upper limit of statistical threshold
Mean value 2.15 2.17
Standard deviation of 0.3 0.4
Extreme value 2.0 2.23
TABLE 2
Spectral signature Frequency (HZ) Reference amplitude
Peak value 1 2.1795989537925024e-06 0.001000408024036487
Peak value 2 4.577157802964255e-05 0.0006659986884322961
Peak value 3 0.00013513513513513514 0.0006145236881082845
Peak value 4 4.359197907585005e-06 0.00061020412697786
TABLE 3
Power spectral signature Frequency (HZ) Reference amplitude
Maximum value 5.2787162162162165e-05 0.057454605036568254
Minimum value 0.013513513513513514 0.02804835346747369
Mean value of -- 0.05594276404659922
And step S4, analyzing the variation trend of the time domain characteristic value and the frequency domain characteristic value within the characteristic value threshold range, and analyzing whether the rubidium clock is abnormal or not according to the variation trend. The method comprises the steps of judging four states of the rubidium clock one by one according to four change conditions of the time-frequency characteristic value, timely finding out abnormal conditions through real-time interpretation of satellite downlink data, and finally monitoring the state of the rubidium clock.
As described above, the step S4 further includes:
in step S41, it is determined that the rubidium clock is normal when the variation of all the characteristic values is within the threshold range. As shown in fig. 2.
In step S42, a rubidium clock is determined to be faulty when the variation of any one of the characteristic values exceeds a statistical threshold range and remains increased. As shown in fig. 3.
In step S43, when the variation of any of the characteristic values exceeds the statistical threshold range but falls back to the normal range within a set time, it is determined that the rubidium clock is disturbed by noise to generate transient abnormal disturbance. As shown in fig. 4.
In step S44, when the variation of any of the characteristic values exceeds the statistical threshold range and remains stable for a long time, it is determined that the performance of the rubidium clock is abnormal. As shown in fig. 5.
According to the technical scheme, the rubidium clock abnormality diagnosis method based on the time-frequency characteristics extracts the time-domain and frequency-domain typical characteristics of the telemetering rubidium clock signal, meanwhile, the threshold interval of the time-frequency characteristics under the normal condition is counted, the change trend of the extracted time-frequency characteristic value is analyzed on the basis of the threshold interval, the abnormality trend is intelligently researched and judged, and therefore the telemetering rubidium clock abnormality is rapidly and accurately detected and identified.
The foregoing description is only exemplary of the preferred embodiments of the invention and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention herein disclosed is not limited to the particular combination of features described above, but also encompasses other arrangements formed by any combination of the above features or their equivalents without departing from the spirit of the invention. For example, the above features and (but not limited to) features having similar functions disclosed in the present invention are mutually replaced to form the technical solution.

Claims (3)

1. A rubidium clock abnormality diagnosis method based on time-frequency characteristics, characterized by comprising the steps of:
step S1, extracting typical characteristic values of the telemetering rubidium clock signal in a time domain and a frequency domain; the typical characteristic value of the time domain adopts a mean value M, a standard value S and an extreme value P in a fixed time window, and the calculation formula is as follows:
Figure FDA0003310360120000011
Figure FDA0003310360120000012
Figure FDA0003310360120000013
in the formulas (1) to (3), N is the number of sampling points in a fixed time window, aiThe value of the ith remote measuring point is M, S and P are respectively the mean value, the standard deviation and the extreme value of the remote measuring value in a fixed time window;
the typical characteristic value of the frequency domain adopts a frequency spectrum X (k) and a power spectrum P (w), and the calculation formula is as follows:
Figure FDA0003310360120000014
Figure FDA0003310360120000015
in the formulas (4) and (5), N is the number of sampling points in a fixed time window, aiThe value of the ith remote measuring point is T, and the length or the period of the fixed time window is T; fT(w) is a fourier transform of the telemetered rubidium clock signal;
step S2, analyzing the variation trend of the typical characteristic values extracted in the period;
step S3, counting the threshold interval of the time frequency characteristic under normal condition, and determining the threshold range of the characteristic value according to the time frequency characteristic value under normal condition; the threshold range of the time domain characteristic value is limited by adopting a lower limit and an upper limit, and the threshold range of the frequency domain characteristic value is limited by adopting a preset proportion of a reference amplitude value;
step S4, analyzing the variation trend of the time domain characteristic value and the frequency domain characteristic value within the characteristic value threshold range, and analyzing whether the rubidium clock is abnormal or not according to the variation trend; and further comprising:
step S41, when the variation of all the characteristic values is within the threshold value range, determining that the rubidium clock is normal;
step S42, when the variation of any characteristic value exceeds the statistical threshold range and keeps increasing, determining that a rubidium clock has a fault;
step S43, when the change of any characteristic value exceeds the statistical threshold range, but falls back to the normal interval within the set time, the rubidium clock is judged to be subjected to noise interference to generate transient abnormal disturbance;
in step S44, when the variation of any of the characteristic values exceeds the statistical threshold range and remains stable for a long time, it is determined that the performance of the rubidium clock is abnormal.
2. The rubidium clock abnormality diagnostic method according to claim 1, wherein the telemetered rubidium clock signal is a signal within a cycle, and the extracted characteristic value is a time-frequency characteristic value of the signal within the cycle.
3. The rubidium clock abnormality diagnostic method of claim 1, wherein the fixed time window is one cycle of a telemetered rubidium clock signal.
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