CN116015492A - Radio station fault diagnosis method, system and equipment - Google Patents
Radio station fault diagnosis method, system and equipment Download PDFInfo
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Abstract
The invention discloses a radio station fault diagnosis method, a system and equipment, and relates to the field of radio station testing. Collecting radio station test data, and carrying out median approximate average interpolation on the radio station test data to generate interpolated radio station test data; determining amplitude information of the interpolated radio station test data; converting the interpolated radio station test data into a frequency domain by using a virtual frequency transformation algorithm to generate frequency domain radio station test data; determining frequency data of the frequency domain radio station test data; and determining the fault type of the radio station according to the amplitude information and the frequency data. The invention can normally extract frequency characteristics on the basis of not reducing the data sampling rate.
Description
Technical Field
The present invention relates to the field of radio station testing, and in particular, to a method, system and device for diagnosing a radio station fault.
Background
The amplitude characteristic extraction of the test data is finished by a time domain hard threshold comparison method at present, in order to reduce the total amount of sampled data, a relatively low data sampling rate is generally selected, and when the sampling frequency is low, the frequency resolution precision after converting the data into the frequency is low, so that the frequency characteristic cannot be normally extracted. Therefore, the frequency characteristic of the test data cannot be extracted due to the limitation of the sampling frequency, so that the follow-up application data characteristic is limited in fault diagnosis, and high-efficiency and accurate fault positioning cannot be completed.
Disclosure of Invention
The invention aims to provide a radio station fault diagnosis method, a system and equipment, which are used for solving the problem that the existing characteristic extraction method reduces the data sampling rate in order to reduce the total amount of sampled data and cannot extract frequency characteristics normally.
In order to achieve the above object, the present invention provides the following solutions:
a radio station failure diagnosis method comprising:
collecting radio station test data, and carrying out median proximity average interpolation on the radio station test data to generate interpolated radio station test data;
determining amplitude information of the interpolated radio station test data;
converting the interpolated radio station test data into a frequency domain by using a virtual frequency transformation algorithm to generate frequency domain radio station test data;
determining frequency data of the frequency domain radio station test data;
and determining the fault type of the radio station according to the amplitude information and the frequency data.
Optionally, the collecting radio station test data, and performing median proximity average interpolation on the radio station test data to generate interpolated radio station test data specifically includes:
performing median proximity average interpolation on the radio station test data by using a formula z_ci= (z (i) +z (i+1))/2+ (1/i) ×z (i) +(1/(i+1))×z (i+1), and generating interpolated radio station test data;
wherein z_ci is interpolated radio station test data; z (i) is the ith sampling point of the radio station test data, and i is the sampling point serial number; z (i+1) is the i+1th sample point of the radio station test data.
Optionally, the converting the interpolated radio station test data to a frequency domain by using a virtual frequency transformation algorithm, and generating the frequency domain radio station test data specifically includes:
frequency domain radio station test data is generated using the formula z_c_fi=z_c1×exp (-j×2×pi× (1/f 2) × (i/N) ×1) +z_c2×exp (-j×2×pi× (1/f 2) × (i/N) ×2) + … +z_cn×exp (-j×2×pi× (1/f 2) × (i/N) ×n);
wherein z_c_fi is frequency domain radio station test data; z_cn is interpolated radio station test data, n=1, 2, 3..n; n is the serial number of the interpolated radio station test data; n is the total number of the interpolated radio station test data; pi is the circumference ratio; j is the representation of the imaginary part of the complex number; f2 is the interpolated sampling frequency.
Optionally, the determining the fault type of the radio station according to the amplitude information and the frequency data specifically includes:
when the amplitude information is between 0 and 1.5, determining that the fault type of the radio station is a radio station receiving module fault;
when the amplitude information is between 1.5 and 2, determining that the fault type of the radio station is a radio station transmitting module fault;
when the frequency data is between 3 and 4.5, determining that the fault type of the radio station is a radio station encryption and decryption module fault;
and when the amplitude information is between 2 and 2.5 and the frequency data is between 2.5 and 3, determining the fault type of the radio station as the fault of the radio station data processing module.
A radio station fault diagnosis system comprising:
the interpolation processing module is used for acquiring radio station test data, carrying out median approximate average interpolation on the radio station test data, and generating the radio station test data after interpolation;
the amplitude information determining module is used for determining the amplitude information of the interpolated radio station test data;
the frequency domain radio station test data generation module is used for converting the interpolated radio station test data into a frequency domain by utilizing a virtual frequency transformation algorithm to generate frequency domain radio station test data;
the frequency domain data determining module is used for determining frequency data of the frequency domain radio station test data;
and the fault type determining module is used for determining the fault type of the radio station according to the amplitude information and the frequency data.
Optionally, the interpolation processing module specifically includes:
an interpolation processing unit, configured to perform median proximity average interpolation on the radio station test data by using a formula z_ci= (z (i) +z (i+1))/2+ (1/i) ×z (i) + (1/(i+1))×z (i+1), and generate interpolated radio station test data;
wherein z_ci is interpolated radio station test data; z (i) is the ith sampling point of the radio station test data, and i is the sampling point serial number; z (i+1) is the i+1th sample point of the radio station test data.
Optionally, the frequency domain radio station test data generating module specifically includes:
a frequency domain radio station test data generating unit configured to generate frequency domain radio station test data using the formula z_c_fi=z_c1×exp (-j×2×pi× (1/f 2) × (i/N) ×1) +z_c2×exp (-j×2×pi× (1/f 2) × (i/N) ×2) + … +z_cn×exp (-j×2×pi× (1/f 2) × (i/N) ×n);
wherein z_c_fi is frequency domain radio station test data; z_cn is interpolated radio station test data, n=1, 2, 3..n; n is the serial number of the interpolated radio station test data; n is the total number of the interpolated radio station test data; pi is the circumference ratio; j is the representation of the imaginary part of the complex number; f2 is the interpolated sampling frequency.
Optionally, the fault type determining module specifically includes:
the radio station receiving module fault determining unit is used for determining that the fault type of the radio station is the radio station receiving module fault when the amplitude information is between 0 and 1.5;
the radio station transmitting module fault determining unit is used for determining that the fault type of the radio station is the radio station transmitting module fault when the amplitude information is between 1.5 and 2;
the radio station encryption and decryption module fault determining unit is used for determining that the fault type of the radio station is the radio station encryption and decryption module fault when the frequency data is between 3 and 4.5;
and the radio station data processing module fault determining unit is used for determining that the fault type of the radio station is the radio station data processing module fault when the amplitude information is between 2 and 2.5 and the frequency data is between 2.5 and 3.
An electronic device comprising a memory for storing a computer program and a processor that runs the computer program to cause the electronic device to perform the radio station fault diagnosis method described above.
A computer readable storage medium storing a computer program which when executed by a processor implements the radio station fault diagnosis method described above.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects: according to the invention, the interpolation processing is carried out on the sampled data, and the data sampling rate is relatively improved on the basis of not reducing the sampled data quantity through the interpolation processing, so that the frequency precision of the data after being converted into the frequency domain is improved, and the frequency characteristics can be normally extracted.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a radio station fault diagnosis method provided by the present invention;
fig. 2 is a block diagram of a radio station fault diagnosis system provided by the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide a radio station fault diagnosis method, a system and equipment, which can normally extract frequency characteristics on the basis of not reducing the data sampling rate.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
Example 1
Fig. 1 is a flowchart of a radio station fault diagnosis method provided by the present invention, and as shown in fig. 1, the present invention provides a radio station fault diagnosis method, including:
step 101: and collecting radio station test data, and carrying out median proximity average interpolation on the radio station test data to generate interpolated radio station test data.
The step 101 specifically includes: performing median proximity average interpolation on the radio station test data by using a formula z_ci= (z (i) +z (i+1))/2+ (1/i) ×z (i) +(1/(i+1))×z (i+1), and generating interpolated radio station test data; wherein z_ci is interpolated radio station test data; z (i) is the ith sampling point of the radio station test data, and i is the sampling point serial number; z (i+1) is the i+1th sample point of the radio station test data.
In practical application, median-adjacent average interpolation is performed on the acquired radio station test data. Let the acquired radio station data be z= [ z1, z2, …, zn ], its sampling frequency be f1. Interpolation of data was completed using the following formula, z_ci= (z (i) +z (i+1))/2+ (1/i) ×z (i) + (1/(i+1))×z (i+1). The original sampling data is interpolated by using the formula, so that the sampling frequency can be increased by 2 times and changed into 2 x f1. Assuming that the interpolated radio station test data is denoted by z_c, z_c= [ z1, z1_c, z2, z2_c, z3, z3_c, … zn ] = [ z_c1, z_c2, …, z_cn ].
Step 102: and determining amplitude information of the interpolated radio station test data.
In practical application, the amplitude information of the interpolated radio station test data is obtained by a hard threshold comparison method. In all the sampling points, the maximum value is taken as the amplitude information A of the signal.
Step 103: and converting the interpolated radio station test data into a frequency domain by using a virtual frequency transformation algorithm to generate frequency domain radio station test data.
The step 103 specifically includes: frequency domain radio station test data is generated using the formula z_c_fi=z_c1×exp (-j×2×pi× (1/f 2) × (i/N) ×1) +z_c2×exp (-j×2×pi× (1/f 2) × (i/N) ×2) + … +z_cn×exp (-j×2×pi× (1/f 2) × (i/N) ×n);
wherein z_c_fi is frequency domain radio station test data; z_cn is interpolated radio station test data, n=1, 2, 3..n; n is the serial number of the interpolated radio station test data; n is the total number of the interpolated radio station test data; pi is the circumference ratio; j is the representation of the imaginary part of the complex number; f2 is the interpolated sampling frequency.
Step 104: frequency data of the frequency domain radio station test data is determined.
In practical application, after obtaining the frequency domain data z_c_f, the maximum value of the frequency domain radio station test data corresponding to the interpolated radio station test data is taken as the frequency data P of the test data based on a hard threshold comparison method.
Step 105: and determining the fault type of the radio station according to the amplitude information and the frequency data.
The step 105 specifically includes: when the amplitude information is between 0 and 1.5, determining that the fault type of the radio station is a radio station receiving module fault; when the amplitude information is between 1.5 and 2, determining that the fault type of the radio station is a radio station transmitting module fault; when the frequency data is between 3 and 4.5, determining that the fault type of the radio station is a radio station encryption and decryption module fault; when the amplitude information is between 2 and 2.5 and the frequency data is between 2.5 and 3, determining that the fault type of the radio station is a radio station data processing module fault; and when the amplitude information and the frequency data are other values, determining that the radio station has no fault.
The invention interpolates the test data of the radio station by utilizing a median approach average interpolation method, equivalently improves the sampling frequency of the signal, and can observe the spectrum information in a wider range after the signal is transformed into the frequency domain.
Compared with the prior art, the method has the advantages that the frequency domain characteristics of the data are extracted, the signal spectrum is expanded, the richer spectrum information is obtained, and the efficient and accurate fault location can be completed by utilizing the information.
Example two
In order to perform a corresponding method of the above embodiment to achieve the corresponding functions and technical effects, a radio station fault diagnosis system is provided below.
Fig. 2 is a block diagram of a radio station fault diagnosis system provided by the present invention, and as shown in fig. 2, the present invention provides a radio station fault diagnosis system, including:
the interpolation processing module 201 is configured to collect radio station test data, perform median-adjacent average interpolation on the radio station test data, and generate interpolated radio station test data.
The interpolation processing module 201 specifically includes: an interpolation processing unit, configured to perform median proximity average interpolation on the radio station test data by using a formula z_ci= (z (i) +z (i+1))/2+ (1/i) ×z (i) + (1/(i+1))×z (i+1), and generate interpolated radio station test data; wherein z_ci is interpolated radio station test data; z (i) is the ith sampling point of the radio station test data, and i is the sampling point serial number; z (i+1) is the i+1th sample point of the radio station test data.
An amplitude information determining module 202 is configured to determine amplitude information of the interpolated radio station test data.
The frequency domain radio station test data generating module 203 is configured to convert the interpolated radio station test data to a frequency domain by using a virtual frequency transformation algorithm, and generate frequency domain radio station test data.
The frequency domain radio station test data generating module 203 specifically includes: a frequency domain radio station test data generating unit configured to generate frequency domain radio station test data using the formula z_c_fi=z_c1×exp (-j×2×pi× (1/f 2) × (i/N) ×1) +z_c2×exp (-j×2×pi× (1/f 2) × (i/N) ×2) + … +z_cn×exp (-j×2×pi× (1/f 2) × (i/N) ×n); wherein z_c_fi is frequency domain radio station test data; z_cn is interpolated radio station test data, n=1, 2, 3..n; n is the serial number of the interpolated radio station test data; n is the total number of the interpolated radio station test data; pi is the circumference ratio; j is the representation of the imaginary part of the complex number; f2 is the interpolated sampling frequency.
A frequency domain data determining module 204 is configured to determine frequency data of the frequency domain radio station test data.
A fault type determining module 205, configured to determine a fault type of the radio station according to the amplitude information and the frequency data.
The fault type determining module 205 specifically includes: the radio station receiving module fault determining unit is used for determining that the fault type of the radio station is the radio station receiving module fault when the amplitude information is between 0 and 1.5; the radio station transmitting module fault determining unit is used for determining that the fault type of the radio station is the radio station transmitting module fault when the amplitude information is between 1.5 and 2; the radio station encryption and decryption module fault determining unit is used for determining that the fault type of the radio station is the radio station encryption and decryption module fault when the frequency data is between 3 and 4.5; and the radio station data processing module fault determining unit is used for determining that the fault type of the radio station is the radio station data processing module fault when the amplitude information is between 2 and 2.5 and the frequency data is between 2.5 and 3.
Example III
An embodiment of the present invention provides an electronic device including a memory for storing a computer program and a processor that runs the computer program to cause the electronic device to execute the method for supporting radio station fault diagnosis provided in the first embodiment.
In practical applications, the electronic device may be a server.
In practical applications, the electronic device includes: at least one processor (processor), memory (memory), bus, and communication interface (Communications Interface).
Wherein: the processor, communication interface, and memory communicate with each other via a communication bus.
And the communication interface is used for communicating with other devices.
And a processor, configured to execute a program, and specifically may execute the method described in the foregoing embodiment.
In particular, the program may include program code including computer-operating instructions.
The processor may be a central processing unit, CPU, or specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement embodiments of the present invention. The one or more processors included in the electronic device may be the same type of processor, such as one or more CPUs; but may also be different types of processors such as one or more CPUs and one or more ASICs.
And the memory is used for storing programs. The memory may comprise high-speed RAM memory or may further comprise non-volatile memory, such as at least one disk memory.
Based on the description of the above embodiments, the embodiments of the present application provide a storage medium having stored thereon computer program instructions executable by a processor to implement the method of any of the embodiments
The supporting radio station fault diagnosis system provided in the embodiments of the present application exists in various forms, including but not limited to:
(1) A mobile communication device: such devices are characterized by mobile communication capabilities and are primarily aimed at providing voice, data communications. Such terminals include: smart phones (e.g., iPhone), multimedia phones, functional phones, and low-end phones, etc.
(2) Ultra mobile personal computer device: such devices are in the category of personal computers, having computing and processing functions, and generally having mobile internet access capabilities. Such terminals include: PDA, MID, and UMPC devices, etc., such as iPad.
(3) Portable entertainment device: such devices may display and play multimedia content. The device comprises: audio, video players (e.g., iPod), palm game consoles, electronic books, and smart toys and portable car navigation devices.
(4) Other electronic devices with data interaction functions.
Thus, particular embodiments of the present subject matter have been described. Other embodiments are within the scope of the following claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may be advantageous.
The system, apparatus, module or unit set forth in the above embodiments may be implemented in particular by a computer chip or entity, or by a product having a certain function. One typical implementation is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being functionally divided into various units, respectively. Of course, the functions of each element may be implemented in one or more software and/or hardware elements when implemented in the present application. It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of a storage medium for a computer include, but are not limited to, a phase change memory (PRAM), a Static Random Access Memory (SRAM), a Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a flash memory or other memory technology, a compact disc read only memory (CD-ROM), a compact disc Read Only Memory (ROM),
Digital Versatile Disk (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices
Or any other non-transmission medium, may be used to store information that may be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular transactions or implement particular abstract data types. The application may also be practiced in distributed computing environments where transactions are performed by remote processing devices that are connected through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (10)
1. A radio station failure diagnosis method, comprising:
collecting radio station test data, and carrying out median proximity average interpolation on the radio station test data to generate interpolated radio station test data;
determining amplitude information of the interpolated radio station test data;
converting the interpolated radio station test data into a frequency domain by using a virtual frequency transformation algorithm to generate frequency domain radio station test data;
determining frequency data of the frequency domain radio station test data;
and determining the fault type of the radio station according to the amplitude information and the frequency data.
2. The radio station fault diagnosis method according to claim 1, wherein the collecting radio station test data and interpolating the radio station test data by median-adjacent average, and generating interpolated radio station test data, specifically comprises:
performing median proximity average interpolation on the radio station test data by using a formula z_ci= (z (i) +z (i+1))/2+ (1/i) ×z (i) +(1/(i+1))×z (i+1), and generating interpolated radio station test data;
wherein z_ci is interpolated radio station test data; z (i) is the ith sampling point of the radio station test data, and i is the sampling point serial number; z (i+1) is the i+1th sample point of the radio station test data.
3. The radio station fault diagnosis method according to claim 2, wherein the converting the interpolated radio station test data into a frequency domain by using a virtual frequency transformation algorithm, and generating frequency domain radio station test data, specifically comprises:
frequency domain radio station test data is generated using the formula z_c_fi=z_c1×exp (-j×2×pi× (1/f 2) × (i/N) ×1) +z_c2×exp (-j×2×pi× (1/f 2) × (i/N) ×2) + … +z_cn×exp (-j×2×pi× (1/f 2) × (i/N) ×n);
wherein z_c_fi is frequency domain radio station test data; z_cn is interpolated radio station test data, n=1, 2, 3..n; n is the serial number of the interpolated radio station test data; n is the total number of the interpolated radio station test data; pi is the circumference ratio; j is the representation of the imaginary part of the complex number; f2 is the interpolated sampling frequency.
4. The radio station fault diagnosis method according to claim 1, wherein said determining the fault type of the radio station based on the amplitude information and the frequency data, comprises:
when the amplitude information is between 0 and 1.5, determining that the fault type of the radio station is a radio station receiving module fault;
when the amplitude information is between 1.5 and 2, determining that the fault type of the radio station is a radio station transmitting module fault;
when the frequency data is between 3 and 4.5, determining that the fault type of the radio station is a radio station encryption and decryption module fault;
and when the amplitude information is between 2 and 2.5 and the frequency data is between 2.5 and 3, determining the fault type of the radio station as the fault of the radio station data processing module.
5. A radio station fault diagnosis system, comprising:
the interpolation processing module is used for acquiring radio station test data, carrying out median approximate average interpolation on the radio station test data, and generating the radio station test data after interpolation;
the amplitude information determining module is used for determining the amplitude information of the interpolated radio station test data;
the frequency domain radio station test data generation module is used for converting the interpolated radio station test data into a frequency domain by utilizing a virtual frequency transformation algorithm to generate frequency domain radio station test data;
the frequency domain data determining module is used for determining frequency data of the frequency domain radio station test data;
and the fault type determining module is used for determining the fault type of the radio station according to the amplitude information and the frequency data.
6. The radio station fault diagnosis system according to claim 5, wherein the interpolation processing module specifically comprises:
an interpolation processing unit, configured to perform median proximity average interpolation on the radio station test data by using a formula z_ci= (z (i) +z (i+1))/2+ (1/i) ×z (i) + (1/(i+1))×z (i+1), and generate interpolated radio station test data;
wherein z_ci is interpolated radio station test data; z (i) is the ith sampling point of the radio station test data, and i is the sampling point serial number; z (i+1) is the i+1th sample point of the radio station test data.
7. The radio station fault diagnosis system according to claim 6, wherein the frequency domain radio station test data generation module specifically comprises:
a frequency domain radio station test data generating unit configured to generate frequency domain radio station test data using the formula z_c_fi=z_c1×exp (-j×2×pi× (1/f 2) × (i/N) ×1) +z_c2×exp (-j×2×pi× (1/f 2) × (i/N) ×2) + … +z_cn×exp (-j×2×pi× (1/f 2) × (i/N) ×n);
wherein z_c_fi is frequency domain radio station test data; z_cn is interpolated radio station test data, n=1, 2, 3..n; n is the serial number of the interpolated radio station test data; n is the total number of the interpolated radio station test data; pi is the circumference ratio; j is the representation of the imaginary part of the complex number; f2 is the interpolated sampling frequency.
8. The radio station fault diagnosis system according to claim 5, wherein the fault type determination module specifically comprises:
the radio station receiving module fault determining unit is used for determining that the fault type of the radio station is the radio station receiving module fault when the amplitude information is between 0 and 1.5;
the radio station transmitting module fault determining unit is used for determining that the fault type of the radio station is the radio station transmitting module fault when the amplitude information is between 1.5 and 2;
the radio station encryption and decryption module fault determining unit is used for determining that the fault type of the radio station is the radio station encryption and decryption module fault when the frequency data is between 3 and 4.5;
and the radio station data processing module fault determining unit is used for determining that the fault type of the radio station is the radio station data processing module fault when the amplitude information is between 2 and 2.5 and the frequency data is between 2.5 and 3.
9. An electronic device comprising a memory for storing a computer program and a processor that runs the computer program to cause the electronic device to perform the radio station fault diagnosis method of any one of claims 1-4.
10. A computer readable storage medium, characterized in that it stores a computer program which, when executed by a processor, implements the radio station fault diagnosis method according to any of claims 1-4.
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