CN115790647A - Method for evaluating stability of fiber-optic gyroscope and application - Google Patents
Method for evaluating stability of fiber-optic gyroscope and application Download PDFInfo
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Abstract
The application discloses a method for evaluating stability of a fiber optic gyroscope, which comprises the following steps: acquiring initial output data of the fiber-optic gyroscope and carrying out deterministic error calibration compensation; acquiring random error data of the fiber-optic gyroscope according to the current output data of the fiber-optic gyroscope after the calibration compensation; and analyzing the random error data by using a hierarchical clustering method to obtain an analysis result representing the uncertainty degree of the random error of the fiber-optic gyroscope, wherein the analysis result is used for evaluating the stability of the fiber-optic gyroscope. The problem of uncertainty degree of quantitative description of random errors of different gyroscopes while considering temperature characteristics of the fiber-optic gyroscope can be solved.
Description
Technical Field
The present invention relates to the field of image processing technologies, and in particular, to a method and an apparatus for evaluating stability of a fiber optic gyroscope, an electronic device, and a computer-readable storage medium.
Background
The errors of the fiber optic gyroscope include deterministic errors and random errors, i.e., the drift of the gyroscope. The deterministic error is mainly caused by factors such as the structure design of the gyroscope, the material characteristics, the processing technology and the like, and can be easily represented by an algebraic equation and compensated by calibration. The random error is mainly caused by the instability of a mechanical part and a circuit part of the gyroscope, and is an important factor for restricting the further improvement of the performance of the gyroscope, and particularly, the influence of the random drift of the gyroscope on the performance of the system is larger for a system with longer working time. Since the gyro random error is irregular and time-varying, it cannot be calibrated and compensated.
The variation coefficient is a statistic for measuring the variation degree of each observed value, and is an important method for measuring the uncertainty degree of the random variable. In general, the higher the uncertainty degree of the random variable, the larger the coefficient of variation; conversely, the smaller the coefficient of variation. In addition, the fiber optic gyroscope is sensitive to temperature, the output of the gyroscope is greatly influenced by the temperature, and random errors of the fiber optic gyroscope show certain hierarchical characteristics along with the influence of the temperature. However, a method capable of quantitatively describing uncertainty degrees of random errors of different gyroscopes does not exist at present, so how to measure uncertainty of random errors output by a gyroscope while considering temperature characteristics of a fiber optic gyroscope is a problem to be solved urgently.
Disclosure of Invention
In view of at least one of the defects or improvement requirements of the prior art, the present invention provides a method for evaluating stability of a fiber-optic gyroscope, a device for evaluating stability of a fiber-optic gyroscope, an electronic device, and a computer-readable storage medium, which are intended to solve the problem of quantitatively describing uncertainty degrees of random errors of different gyroscopes while considering temperature characteristics of the fiber-optic gyroscope.
In order to achieve the above object, according to a first aspect of the present invention, there is provided a fiber-optic gyroscope stability evaluation method, including: acquiring initial output data of the fiber-optic gyroscope and performing deterministic error calibration compensation; acquiring random error data of the fiber-optic gyroscope according to the current output data of the fiber-optic gyroscope after the calibration compensation; and analyzing the random error data by using a hierarchical clustering method to obtain an analysis result representing the uncertainty degree of the random error of the fiber-optic gyroscope, wherein the analysis result is used for evaluating the stability of the fiber-optic gyroscope.
In an embodiment of the present invention, the acquiring initial output data of the fiber-optic gyroscope and performing deterministic error calibration compensation includes: the optical fiber gyroscope is installed on a three-axis rate rotary table in a static environment, the three-axis rate rotary table is kept static, the input angular speed of the optical fiber gyroscope is enabled to be zero, and data output by the optical fiber gyroscope within preset time is collected to be used as initial output data to carry out deterministic error calibration compensation.
In an embodiment of the present invention, the obtaining random error data of the fiber-optic gyroscope according to the current output data of the fiber-optic gyroscope after the calibration compensation includes: respectively calculating the mean values of the current output data of the x axis, the y axis and the z axis of the fiber-optic gyroscope after the calibration compensation; and respectively calculating the difference value between each current output data and the mean value of the corresponding axis to serve as the random error data of the corresponding axis.
In an embodiment of the present invention, the analyzing the random error data by using a hierarchical clustering method to obtain an analysis result representing an uncertainty degree of the random error of the fiber-optic gyroscope, includes: performing hierarchical clustering on the N random error data to obtain N types of data; according to the formula
Determining the weight of each type of data, where m c C =1,2, \8230;, n, which is the total number of data belonging to c-type data in gyro random error data; according to the formula
And calculating the coefficient of variation of each type of data, wherein,
is the random error mean, σ, of class c data c The standard deviation of random error of the class c data; according to the formula
And calculating the average variation coefficient of the fiber-optic gyroscope.
In one embodiment of the present invention, the evaluating the stability of the fiber-optic gyroscope includes: determining the uncertainty degree of the random error of the fiber-optic gyroscope according to the average variation coefficient, wherein the larger the average variation coefficient is, the higher the uncertainty degree of the random error of the fiber-optic gyroscope is, and the more unstable the fiber-optic gyroscope is; conversely, the smaller the average variation coefficient is, the lower the uncertainty degree of the random error of the fiber-optic gyroscope is, and the more stable the fiber-optic gyroscope is.
According to a second aspect of the present invention, there is also provided a fiber-optic gyroscope stability evaluation apparatus, including: the deterministic error calibration compensation module is used for acquiring initial output data of the fiber-optic gyroscope and performing deterministic error calibration compensation; the random error data acquisition module is used for acquiring the random error data of the fiber-optic gyroscope according to the current output data of the fiber-optic gyroscope after the calibration compensation; and the random error analysis module is used for analyzing the random error data by utilizing a hierarchical clustering method to obtain an analysis result representing the uncertainty degree of the random error of the fiber-optic gyroscope and evaluating the stability of the fiber-optic gyroscope.
In an embodiment of the present invention, the random error data obtaining module is specifically configured to: respectively calculating the average value of the current output data of the x axis, the y axis and the z axis after the fiber-optic gyroscope is subjected to calibration compensation; and respectively calculating the difference value between each current output data and the mean value of the corresponding axis to serve as the random error data of the corresponding axis.
In an embodiment of the present invention, the random error analysis module is specifically configured to: performing hierarchical clustering on the N random error data to obtain N types of data; according to the formula
Determining the weight of each type of data, wherein m c C =1,2, \8230;, n, which is the total number of data belonging to c-type data in gyro random error data; according to the formula
And calculating the coefficient of variation of each type of data, wherein,
is the random error mean, σ, of class c data c The standard deviation of random errors of the c-type data; according to the formula
And calculating the average variation coefficient of the fiber-optic gyroscope.
According to a third aspect of the present invention, there is also provided an electronic apparatus comprising: a memory storing a computer program and one or more processors coupled to the memory for executing the computer program to implement the steps of the method of any of the above embodiments.
According to a fourth aspect of the present invention, there is also provided a computer-readable storage medium storing a computer program executable by an access authentication apparatus, the computer program, when run on the access authentication apparatus, causing the access authentication apparatus to perform the steps of the method of any one of the above embodiments.
In general, compared with the prior art, the above technical solutions conceived by the present invention can achieve at least the following beneficial effects:
1) The method comprises the steps of obtaining random error data of the fiber-optic gyroscope after deterministic error calibration compensation is carried out on the fiber-optic gyroscope, analyzing the random error data of the fiber-optic gyroscope by utilizing a hierarchical clustering method to obtain an analysis result representing the uncertainty degree of the random error of the fiber-optic gyroscope, realizing quantitative description on the uncertainty degree of the random error of the fiber-optic gyroscope, and effectively evaluating the performance of the fiber-optic gyroscope, thereby having important reference significance for further improving the performance of the gyroscope;
2) By considering the hierarchical characteristics of the random error of the fiber-optic gyroscope under the influence of temperature and adopting a corresponding hierarchical clustering algorithm to analyze the uncertainty degree of the random error of the fiber-optic gyroscope, the accuracy and the applicability of the quantitative analysis of the uncertainty degree of the random error of the fiber-optic gyroscope can be ensured.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a flowchart of a method for evaluating stability of a fiber-optic gyroscope according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of an apparatus for evaluating stability of a fiber optic gyroscope according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a computer-readable storage medium according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
The terms "first," "second," "third," and the like in the description and claims of this application and in the foregoing drawings are used for distinguishing between different elements and not for describing a particular sequential order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
As shown in fig. 1, a first embodiment of the present invention provides a method for evaluating stability of a fiber-optic gyroscope, including: s1, acquiring initial output data of the fiber-optic gyroscope and performing deterministic error calibration compensation; s2, acquiring random error data of the fiber-optic gyroscope according to the current output data of the fiber-optic gyroscope after calibration compensation; and S3, analyzing the random error data by using a hierarchical clustering method to obtain an analysis result representing the uncertainty degree of the random error of the fiber-optic gyroscope, wherein the analysis result is used for evaluating the stability of the fiber-optic gyroscope.
In step S1, for example, in a static environment, the fiber optic gyroscope is mounted on a three-axis rate turntable, the three-axis rate turntable is kept stationary, an input angular rate of the gyroscope is guaranteed to be 0, data output by the fiber optic gyroscope within a preset time is collected as initial output data of the fiber optic gyroscope, and deterministic error calibration compensation is performed. The preset time is, for example, one hour, but in other embodiments, the preset time may be set by the user according to the need, and the application is not limited thereto.
In step S2, the current output data of the fiber optic gyroscope after the calibration compensation includes output data of three axes x, y, and z of the fiber optic gyroscope, for example, average values of the current output data of the three axes x, y, and z of the fiber optic gyroscope after the calibration compensation are respectively calculated, each current output data output by the three axes x, y, and z of the fiber optic gyroscope is respectively taken out, and a difference between the current output data and the average value of the corresponding axis is calculated, so as to obtain random error data of the corresponding axis.
In step S3, the specific steps of analyzing the fiber-optic gyroscope random error data by using the hierarchical clustering method are as follows:
(1) Performing hierarchical clustering on the N random error data to obtain N types of data;
(2) According to the formula
Determining the weight of each type of data, where m c C =1,2, \ 8230;, n, which is the total number of data belonging to the c-type data in the gyro random error data;
(3) According to the formula
And calculating the coefficient of variation of each type of data, wherein,
is the random error mean, σ, of class c data c The standard deviation of random errors of the c-type data;
(4) According to the formula
And calculating the average variation coefficient of the fiber-optic gyroscope.
Furthermore, the uncertainty degree of the random error of the fiber-optic gyroscope is determined according to the obtained average variation coefficient and is used for evaluating the stability of the fiber-optic gyroscope. The larger the average variation coefficient is, the higher the uncertainty degree of the random error of the fiber-optic gyroscope is, and the more unstable the fiber-optic gyroscope is; conversely, the smaller the average variation coefficient is, the lower the uncertainty degree of the random error of the fiber-optic gyroscope is, and the more stable the fiber-optic gyroscope is.
In summary, the method for evaluating the stability of the fiber optic gyroscope provided in the first embodiment of the present application obtains the random error data of the fiber optic gyroscope after performing deterministic error calibration and compensation on the fiber optic gyroscope, and analyzes the random error data of the fiber optic gyroscope by using a hierarchical clustering method to obtain an analysis result representing the degree of uncertainty of the random error of the fiber optic gyroscope, so that the degree of uncertainty of the random error of the fiber optic gyroscope is quantitatively described, the performance of the fiber optic gyroscope can be effectively evaluated, and therefore, the method has an important reference meaning for further improving the performance of the gyroscope; by considering the hierarchical characteristic of the random error of the fiber-optic gyroscope under the influence of temperature and adopting a corresponding hierarchical clustering algorithm to analyze the uncertainty degree of the random error of the fiber-optic gyroscope, the accuracy and the applicability of the quantitative analysis of the uncertainty degree of the random error of the fiber-optic gyroscope can be ensured.
As shown in fig. 2, a second embodiment of the present invention further provides a fiber-optic gyroscope stability evaluation apparatus 20, for example, including: a deterministic error calibration compensation module 201, a random error data acquisition module 202, and a random error analysis module 203.
The deterministic error calibration and compensation module 201 is configured to collect initial output data of the fiber optic gyroscope and perform deterministic error calibration and compensation. The random error data obtaining module 202 is configured to obtain random error data of the fiber optic gyroscope according to the current output data of the fiber optic gyroscope after the calibration compensation is performed. The random error analysis module 203 is configured to analyze the random error data by using a hierarchical clustering method to obtain an analysis result representing an uncertainty degree of a random error of the fiber-optic gyroscope, and is configured to evaluate the stability of the fiber-optic gyroscope.
In one embodiment, the random error data acquisition module 202 is specifically configured to, for example: respectively calculating the mean values of the current output data of the x axis, the y axis and the z axis of the fiber-optic gyroscope after the calibration compensation; and respectively calculating the difference value between each current output data and the average value of the corresponding axis as the random error data of the corresponding axis.
In one embodiment, the random error analysis module 203 is specifically configured to: performing hierarchical clustering on the N random error data to obtain N types of data; according to the formula
Determining the weight of each type of data, where m c C =1,2, \ 8230;, n, which is the total number of data belonging to the c-type data in the gyro random error data; root of herbaceous plantsAccording to the formula
And calculating the coefficient of variation of each type of data, wherein,
is the random error mean, σ, of class c data c The standard deviation of random error of the class c data; according to the formula
And calculating the average variation coefficient of the fiber-optic gyroscope.
It should be noted that the method for evaluating stability of an optical fiber gyro implemented by the apparatus for evaluating stability of an optical fiber gyro disclosed in the second embodiment of the present invention is as described in the first embodiment, and therefore, a detailed description thereof is omitted. Optionally, each component and the other operations or functions in the second embodiment are respectively for implementing the method described in the first embodiment, and the beneficial effects of this embodiment are the same as those of the first embodiment, which are not described herein again for brevity.
As shown in fig. 3, the third embodiment of the present invention further provides an electronic device 30, including: a memory 32 and one or more processors 31 connected to the memory 32. The memory 32 stores a computer program, and the processor 31 is configured to execute the computer program to implement the fiber-optic gyroscope stability evaluation method according to the first embodiment. For the sake of brevity, details of the method for evaluating the stability of the fiber-optic gyroscope may be omitted, and the beneficial effects of this embodiment are the same as those of the method for evaluating the stability of the fiber-optic gyroscope provided in the first embodiment.
In addition, the third embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps of the method described in the first embodiment, and the computer-readable storage medium provided by this embodiment has the same beneficial effects as the method for evaluating the stability of the fiber-optic gyroscope provided by the first embodiment.
The computer-readable storage medium may include, but is not limited to, any type of disk including floppy disks, optical disks, DVD, CD-ROMs, microdrive, and magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of media or device suitable for storing instructions and/or data.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art will recognize that the embodiments described in this specification are preferred embodiments and that acts or modules referred to are not necessarily required for this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to the related descriptions of other embodiments.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by a program, which is stored in a computer-readable memory, and the memory may include: flash disks, read-Only memories (ROMs), random Access Memories (RAMs), magnetic or optical disks, and the like.
The above description is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure should not be limited thereby. That is, all equivalent changes and modifications made in accordance with the teachings of the present disclosure are intended to be included within the scope of the present disclosure. Embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A method for evaluating the stability of a fiber-optic gyroscope is characterized by comprising the following steps:
acquiring initial output data of the fiber-optic gyroscope and carrying out deterministic error calibration compensation;
acquiring random error data of the fiber-optic gyroscope according to the current output data of the fiber-optic gyroscope after the calibration compensation;
and analyzing the random error data by using a hierarchical clustering method to obtain an analysis result representing the uncertainty degree of the random error of the fiber-optic gyroscope, wherein the analysis result is used for evaluating the stability of the fiber-optic gyroscope.
2. The method for evaluating the stability of the fiber-optic gyroscope according to claim 1, wherein the collecting initial output data of the fiber-optic gyroscope and performing deterministic error calibration compensation comprises:
the optical fiber gyroscope is installed on a three-axis rate rotary table in a static environment, the three-axis rate rotary table is kept static, the input angular speed of the optical fiber gyroscope is enabled to be zero, and data output by the optical fiber gyroscope within preset time is collected to be used as initial output data to carry out deterministic error calibration compensation.
3. The method for evaluating the stability of the fiber-optic gyroscope according to claim 1, wherein the obtaining of the random error data of the fiber-optic gyroscope according to the current output data of the fiber-optic gyroscope after the calibration compensation comprises:
respectively calculating the average value of the current output data of the x axis, the y axis and the z axis after the fiber-optic gyroscope is subjected to calibration compensation;
and respectively calculating the difference value between each current output data and the average value of the corresponding axis as the random error data of the corresponding axis.
4. The method for evaluating the stability of the fiber-optic gyroscope according to claim 1, wherein the analyzing the random error data by using a hierarchical clustering method to obtain an analysis result representing the uncertainty degree of the random error of the fiber-optic gyroscope comprises:
performing hierarchical clustering on the N random error data to obtain N types of data;
according to the formula
Determining the weight of each type of data, where m c C =1,2, \ 8230;, n, which is the total number of data belonging to the c-type data in the gyro random error data;
according to the formula
And calculating the coefficient of variation of each type of data, wherein,
is the random error mean, σ, of class c data c The standard deviation of random error of the class c data;
according to the formula
And calculating the average variation coefficient of the fiber-optic gyroscope.
5. The method for evaluating the stability of the fiber-optic gyroscope according to claim 4, wherein the evaluating the stability of the fiber-optic gyroscope comprises:
determining the uncertainty degree of the random error of the fiber-optic gyroscope according to the average variation coefficient, wherein the larger the average variation coefficient is, the higher the uncertainty degree of the random error of the fiber-optic gyroscope is, and the more unstable the fiber-optic gyroscope is; conversely, the smaller the average variation coefficient is, the lower the uncertainty degree of the random error of the fiber-optic gyroscope is, and the more stable the fiber-optic gyroscope is.
6. An optical fiber gyro stability evaluation device, comprising:
the deterministic error calibration compensation module is used for acquiring initial output data of the fiber-optic gyroscope and performing deterministic error calibration compensation;
the random error data acquisition module is used for acquiring the random error data of the fiber-optic gyroscope according to the current output data of the fiber-optic gyroscope after the calibration compensation is carried out on the fiber-optic gyroscope;
and the random error analysis module is used for analyzing the random error data by utilizing a hierarchical clustering method to obtain an analysis result representing the uncertainty degree of the random error of the fiber-optic gyroscope and evaluating the stability of the fiber-optic gyroscope.
7. The apparatus for evaluating stability of a fiber optic gyroscope according to claim 6, wherein the random error data acquisition module is specifically configured to:
respectively calculating the mean values of the current output data of the x axis, the y axis and the z axis of the fiber-optic gyroscope after the calibration compensation;
and respectively calculating the difference value between each current output data and the average value of the corresponding axis as the random error data of the corresponding axis.
8. The apparatus for evaluating stability of a fiber-optic gyroscope according to claim 6, wherein the random error analysis module is specifically configured to:
performing hierarchical clustering on the N random error data to obtain N types of data;
according to the formula
Determining the weight of each type of data, where m c C =1,2, \ 8230;, n, which is the total number of data belonging to the c-type data in the gyro random error data;
according to the formula
And calculating the coefficient of variation of each type of data, wherein,
is the random error mean, σ, of class c data c The standard deviation of random error of the class c data;
according to the formula
And calculating the average variation coefficient of the fiber-optic gyroscope.
9. An electronic device, comprising: a memory storing a computer program and one or more processors coupled to the memory for executing the computer program to perform the steps of the method of any of claims 1-5.
10. A computer-readable storage medium, in which a computer program is stored which is executable by an access authentication device, which computer program, when run on the access authentication device, causes the access authentication device to carry out the steps of the method of any one of claims 1 to 5.
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