A radar fault diagnosis method and system based on sparse decomposition

Abstract

The present invention relates to a radar fault diagnosis method and system based on sparse decomposition. This method uses a redundant basis to perform sparse decomposition on time-domain data to obtain frequency-domain data. This method then determines whether a radar system fault has occurred based on the frequency-domain data. This method improves the accuracy of radar fault location under the condition of limited time-domain data length, thereby resolving existing issues such as delayed fault elimination, prolonged mean time between failures, and severe impact on system task progress.

Description

Technical Field

[0001] The present invention relates to the technical field of radar fault diagnosis, and in particular to a radar fault diagnosis method and system based on sparse decomposition. Background Art

[0002] Existing radar fault location methods are mainly based on the classical Fourier transform to complete the time-frequency domain transformation of fault data and perform fault location in the frequency domain. However, because the frequency resolution of the classical Fourier transform is limited by the observation time, it often cannot achieve the fault location accuracy required by the system, resulting in inaccurate fault diagnosis, untimely fault elimination, and extended mean time between failures, which in turn affects the system's task progress. Summary of the Invention

[0003] In order to solve the above problems existing in the prior art, the present invention provides a radar fault diagnosis method and system based on sparse decomposition.

[0004] To achieve the above object, the present invention provides the following solutions:

[0005] A radar fault diagnosis method based on sparse decomposition, comprising:

[0006] Obtain time domain data of radar fault detection points;

[0007] Build a redundant base;

[0008] Using the redundant basis to perform sparse decomposition on the time domain data to obtain frequency domain data;

[0009] It is determined whether a system in the radar fails based on the frequency domain data.

[0010] Preferably, the constructing of a redundant base specifically includes:

[0011] The time delay interval based on radar is adopted by formula a i =sin(2×p i ×t×[1:100]) T Determining a component column of the redundant basis;

[0012] Where t is the time delay interval of the radar, t = 0.01 × i, i = 1, 2..., n, p i is a constant.

[0013] Preferably, the step of using the redundant basis to perform sparse decomposition on the time domain data to obtain frequency domain data specifically includes:

[0014] Using the formula y = A -1 x obtains the frequency domain data according to the time domain data;

[0015] Among them, x is the time domain data, y is the frequency domain data, A is the redundant basis, A -1 is the inverse matrix of the redundant basis.

[0016] Preferably, the number of columns of the redundant basis is determined using the formula M=N×100 / (N+5);

[0017] When the number of columns M contains decimals, the value of the column number is determined by rounding off;

[0018] Where M is the number of columns and N is the number of subsystems in the radar.

[0019] Preferably, determining whether a radar failure occurs according to the frequency domain data specifically includes:

[0020] Determining the number of non-zero point data in the frequency domain data;

[0021] When the number of non-zero point data in the frequency domain data is less than a first preset value, determining that a receiving system of the radar has failed;

[0022] When the number of non-zero point data in the frequency domain data is greater than or equal to the first preset value and less than or equal to the second preset value, it is determined that a failure occurs in the radar transmission system;

[0023] When the number of non-zero point data in the frequency domain data is greater than the second preset value, it is determined that a failure occurs in the antenna servo system of the radar.

[0024] Preferably, the first preset value is 10; the second preset value is 20.

[0025] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0026] The radar fault diagnosis method based on sparse decomposition provided by the present invention uses a redundant basis to perform sparse decomposition on the time domain data to obtain frequency domain data, and then determines whether a system in the radar has a fault based on the frequency domain data. This can improve the accuracy of radar fault location under the condition that the length of the time domain data is limited.

[0027] Corresponding to the radar fault diagnosis method based on sparse decomposition provided above, the present invention also provides a radar fault diagnosis system based on sparse decomposition, the system comprising:

[0028] A time domain data acquisition module is used to obtain time domain data of radar fault detection points;

[0029] A redundant base building module, used for building a redundant base;

[0030] A frequency domain data determination module, configured to perform sparse decomposition on the time domain data using the redundant basis to obtain frequency domain data;

[0031] A fault judgment module is used to judge whether a system in the radar has a fault based on the frequency domain data.

[0032] Preferably, the redundant base building block comprises:

[0033] The column determination unit is used to determine the time delay interval of the radar using formula a i =sin(2×p i ×t×[1:100]) T Determining a component column of the redundant basis;

[0034] Where t is the time delay interval of the radar, t = 0.01 × i, i = 1, 2..., n, p i is a constant.

[0035] Preferably, the frequency domain data determination module includes:

[0036] Frequency domain data determination unit, used to use the formula y=A -1 x obtains the frequency domain data according to the time domain data;

[0037] Among them, x is the time domain data, y is the frequency domain data, A is the redundant basis, A -1 is the inverse matrix of the redundant basis.

[0038] Preferably, the fault judgment module includes:

[0039] A number determining unit, configured to determine the number of non-zero point data in the frequency domain data;

[0040] a first radar system fault determination unit, configured to determine that a fault occurs in the radar receiving system when the number of non-zero point data in the frequency domain data is less than a first preset value;

[0041] a second radar system fault determination unit, configured to determine that a fault occurs in the radar's transmission system when the number of non-zero point data in the frequency domain data is greater than or equal to the first preset value and less than or equal to a second preset value;

[0042] The third radar system fault determination unit is configured to determine that a fault occurs in the antenna servo system of the radar when the number of non-zero point data in the frequency domain data is greater than the second preset value.

[0043] Since the technical effects achieved by the radar fault diagnosis system based on sparse decomposition provided by the present invention are the same as the technical effects achieved by the radar fault diagnosis method based on sparse decomposition provided above, they will not be described in detail here. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1 A flowchart of the radar fault diagnosis method based on sparse decomposition provided by the present invention;

[0046] Figure 2 This is a structural diagram of the radar fault diagnosis system based on sparse decomposition provided by the present invention. DETAILED DESCRIPTION

[0047] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0048] The purpose of the present invention is to provide a radar fault diagnosis method and system based on sparse decomposition, which can improve the accuracy of radar fault location.

[0049] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0050] like Figure 1 As shown, the radar fault diagnosis method based on sparse decomposition provided by the present invention includes:

[0051] Step 100: Obtain time domain data of radar fault detection points. The time domain data of radar fault detection points is collected from the radar subsystem's fault monitoring points. Assume that the collected signal is x = [x1, x2, x3], where x1, x2, and x3 are the time domain data of the radar receiving system, transmitting system, and antenna servo system's fault monitoring points, respectively. These are 1×10, 1×20, and 1×30 row matrices (the length of the data point is related to the required fault diagnosis accuracy, and when the required accuracy is high), x is a 1×60 row matrix.

[0052] Step 101: Construct a redundant basis. The constructed redundant basis is a column vector with a zero norm of 1 that forms an N-dimensional space. The time domain fault data is related to the time delay interval t between the system startup time and the fault alarm time after startup. When t is divided into small intervals of 0.01, the redundant basis is constructed according to the following formula:

[0053] Assume that the components of redundant base A are represented by a i If a i =sin(2*p i *(0.01*i)*[1:100]) T For example, i ranges from 1 to 500, where 500 is the number of columns in the redundant base A, i.e., a i is a column vector with 100 rows and 1 column. The value of 500 is related to the complexity of the system and is usually obtained based on experience. In the radar system targeted by this invention, 500 is more appropriate. i Is a constant, equal to pi 3.1415926...., in a i In fact, 0.01*i is t. In the first column of the redundant basis A, t is 0.01, in the second column, t is 0.02, in the third column, t is 0.03, in the fourth column, t is 0.04, and so on. This means that t is divided into intervals of 0.01.

[0054] Assuming that the system has N subsystems, the number of columns M of the redundant base is calculated according to the following formula: M = N*100 / (N+5). When M is a decimal, the integer part is rounded off.

[0055] Step 102: Use redundant basis to perform sparse decomposition on the time domain data to obtain frequency domain data. Sparse decomposition is to select a basis that completely matches the signal to be decomposed from the redundant basis to construct the signal to be decomposed. In this case, y is a 1×60 frequency domain row matrix. For example, using the formula y=A -1 x is the time domain data, y is the frequency domain data, A is the redundant basis, A -1 is the inverse matrix of the redundant basis.

[0056] Step 103: Determine whether a system fault has occurred in the radar based on the frequency domain data. After y is obtained, the number of non-zero elements in it is calculated, and then an accurate fault location result can be obtained using the determination rule. Specifically, the implementation process of step 103 can be:

[0057] Determine the number z of non-zero data in the frequency domain data.

[0058] When the number z of non-zero point data in the frequency domain data is less than a first preset value, it is determined that a failure occurs in the receiving system of the radar.

[0059] When the number z of non-zero data in the frequency domain data is greater than or equal to a first preset value and less than or equal to a second preset value, it is determined that the radar transmission system has failed. For example, the first preset value is set to 10 and the second preset value is set to 20.

[0060] When the number z of non-zero point data in the frequency domain data is greater than a second preset value, it is determined that a fault occurs in the antenna servo system of the radar.

[0061] Typically, the classical Fourier transform is used to obtain frequency domain data y. However, because the resolution accuracy of this method is limited by the length of the time domain data, the number of nonzero points z in the frequency domain data obtained through the classical Fourier transform cannot fully correspond to the fault determination method when the time domain data is limited. For example, when a fault occurs in the receiving system, z should normally be less than 10. However, due to the limitation of the time domain data length, the Fourier transform often exceeds 10. In this case, according to existing fault determination rules, the radar transmission system or antenna servo system will be concluded to be faulty, resulting in an incorrect fault location result and unable to achieve accurate and effective fault location. To improve the fault location accuracy of this method, it is often necessary to collect time domain data with a length of more than 100 data points, which can lead to various difficulties in data sampling, storage, and denoising.

[0062] Based on this, the present invention uses redundant basis to decompose time domain data, and can obtain accurate frequency domain data under the condition of limited time domain data length, so that the number of non-zero data in y is completely consistent with the fault judgment rules of each radar subsystem, thereby improving the accuracy of fault location.

[0063] Corresponding to the radar fault diagnosis method based on sparse decomposition provided above, the present invention also provides a radar fault diagnosis system based on sparse decomposition, such as Figure 2 As shown, the system includes: a time domain data acquisition module 200, a redundant base construction module 201, a frequency domain data determination module 202 and a fault judgment module 203.

[0064] The time domain data acquisition module 200 is used to acquire the time domain data of the radar fault detection point.

[0065] The redundant base building module 201 is used to build a redundant base.

[0066] The frequency domain data determination module 202 is configured to perform sparse decomposition on the time domain data using a redundant basis to obtain frequency domain data.

[0067] The fault judgment module 203 is used to judge whether a fault occurs in the radar system based on the frequency domain data.

[0068] As an embodiment of the present invention, the redundant base building module 201 adopted above includes: a component column determination unit.

[0069] The column determination unit is used to determine the time delay interval based on the radar using formula a i =sin(2×p i ×t×[1:100])T Determine the constituent columns of the redundant basis.

[0070] Where t is the time delay interval of the radar, t = 0.01 × i, i = 1, 2..., n, and pi is a constant.

[0071] As another embodiment of the present invention, the frequency domain data determination module 202 adopted above includes: a frequency domain data determination unit.

[0072] The frequency domain data determination unit is used to use the formula y=A -1 x obtains frequency domain data based on time domain data.

[0073] Among them, x is the time domain data, y is the frequency domain data, A is the redundant basis, A -1 is the inverse matrix of the redundant basis.

[0074] As another embodiment of the present invention, the fault judgment module 203 adopted above includes: a number determination unit, a first radar system fault judgment unit, a second radar system fault judgment unit and a third radar system fault judgment unit.

[0075] The number determining unit is used to determine the number of non-zero point data in the frequency domain data.

[0076] The first radar system fault determination unit is used to determine that a fault occurs in the radar receiving system when the number of non-zero point data in the frequency domain data is less than a first preset value.

[0077] The second radar system fault determination unit is used to determine that a fault occurs in the radar's transmission system when the number of non-zero point data in the frequency domain data is greater than or equal to a first preset value and less than or equal to a second preset value.

[0078] The third radar system fault determination unit is configured to determine that a fault occurs in the antenna servo system of the radar when the number of non-zero point data in the frequency domain data is greater than a second preset value.

[0079] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0080] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only intended to help understand the method and core concept of the present invention. At the same time, those skilled in the art will find that the specific implementation methods and application scopes may vary based on the concept of the present invention. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims

1. A radar fault diagnosis method based on sparse decomposition, characterized in that: include: Obtain time domain data of radar fault detection points; Constructing a redundant base, including: using formula a based on the time delay interval of the radar i =sin(2×p i ×t×[1:100]) T Determine the columns that make up the redundant basis; the number of columns of the redundant basis is determined using the formula M=N×100 / (N+5); when the number of columns M contains decimals, the value of the number of columns is determined by rounding off; wherein t is the time delay interval of the radar; t=0.01×i; i=1,2...,M, representing the i-th column of the redundant basis; p i is a constant; N is the number of subsystems in the radar; Using the redundant basis to perform sparse decomposition on the time domain data to obtain frequency domain data; It is determined whether a system in the radar fails based on the frequency domain data.

2. The radar fault diagnosis method based on sparse decomposition according to claim 1, characterized in that: The step of using the redundant basis to perform sparse decomposition on the time domain data to obtain frequency domain data specifically includes: Using the formula y = A -1 x obtains the frequency domain data according to the time domain data; Among them, x is the time domain data, y is the frequency domain data, A is the redundant basis, A -1 is the inverse matrix of the redundant basis.

3. The radar fault diagnosis method based on sparse decomposition according to claim 1, characterized in that: Determining whether a radar failure occurs according to the frequency domain data specifically includes: Determining the number of non-zero point data in the frequency domain data; When the number of non-zero point data in the frequency domain data is less than a first preset value, determining that a receiving system of the radar has failed; When the number of non-zero point data in the frequency domain data is greater than or equal to the first preset value and less than or equal to the second preset value, it is determined that a failure occurs in the radar transmission system; When the number of non-zero point data in the frequency domain data is greater than the second preset value, it is determined that a failure occurs in the antenna servo system of the radar.

4. The radar fault diagnosis method based on sparse decomposition according to claim 3 is characterized in that: The first preset value is 10; the second preset value is 20.

5. A radar fault diagnosis system based on sparse decomposition, characterized in that: include: A time domain data acquisition module is used to obtain time domain data of radar fault detection points; A redundant base building module, used for building a redundant base; A frequency domain data determination module, configured to perform sparse decomposition on the time domain data using the redundant basis to obtain frequency domain data; a fault judgment module, configured to judge whether a system in the radar has a fault based on the frequency domain data; The redundant base building block includes: The column determination unit is used to determine the time delay interval of the radar using formula a i =sin(2×p i ×t×[1:100]) T Determine the columns that make up the redundant basis; the number of columns of the redundant basis is determined using the formula M=N×100 / (N+5); when the number of columns M contains decimals, the value of the number of columns is determined by rounding off; wherein t is the time delay interval of the radar; t=0.01×i; i=1,2...,M, representing the i-th column of the redundant basis; p i is a constant; N is the number of subsystems in the radar.

6. The radar fault diagnosis system based on sparse decomposition according to claim 5, characterized in that: The frequency domain data determination module includes: Frequency domain data determination unit, used to use the formula y=A -1 x obtains the frequency domain data according to the time domain data; Among them, x is the time domain data, y is the frequency domain data, A is the redundant basis, A -1 is the inverse matrix of the redundant basis.

7. The radar fault diagnosis system based on sparse decomposition according to claim 5, characterized in that: The fault judgment module includes: A number determining unit, configured to determine the number of non-zero point data in the frequency domain data; a first radar system fault determination unit, configured to determine that a fault occurs in the radar receiving system when the number of non-zero point data in the frequency domain data is less than a first preset value; a second radar system fault determination unit, configured to determine that a fault occurs in the radar's transmission system when the number of non-zero point data in the frequency domain data is greater than or equal to the first preset value and less than or equal to a second preset value; The third radar system fault determination unit is configured to determine that a fault occurs in the antenna servo system of the radar when the number of non-zero point data in the frequency domain data is greater than the second preset value.

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