An integrated signal evaluation system and method

Abstract

The embodiment of the specification discloses a kind of comprehensive signal evaluation system and method, the system includes at least one comprehensive signal analyzer, remote terminal;Comprehensive signal analyzer includes communication module, signal generation module, spectrum analysis module, index test module, map location module, analysis training module;Remote terminal is configured to: obtain the equipment location information of comprehensive signal analyzer, user information by map location module;Based on equipment location information, user information, determine simulation test parameters, and send simulation test parameters to comprehensive signal analyzer;In response to obtaining the user analysis result of comprehensive signal analyzer, determine simulation test result based on user analysis result;Simulation test result includes the user test score of user.

Description

TECHNICAL FIELD

[0001] The present specification relates to the field of signal analysis, and in particular, to a comprehensive signal evaluation system and method. BACKGROUND

[0002] In the current field of signal analysis, comprehensive signal analyzers have become a key tool for tasks such as radio signal identification, searching, and simulation exercises. The instrument can perform frequency domain analysis and time domain analysis to identify the frequency range, energy spectrum range, and potential interference signal frequency range of a signal. When encountering unknown waveforms, users often need to perform a series of analyses, including obtaining key information such as the frequency spectrum, energy spectrum, and power spectrum of the signal. To ensure the accuracy and effectiveness of the analysis, users need to adjust multiple parameters, such as scan time, frequency scan range, resolution bandwidth, attenuator attenuation amplitude, and center frequency. However, when multiple machines are used for joint testing, it is difficult to accurately set the signal transmission parameters of multiple signal analyzers during joint simulation analysis, and the processing method of the simulation test results is not clear, making it difficult to accurately evaluate the performance of the signal analyzer and the effectiveness of the simulation analysis.

[0003] Therefore, it is desirable to provide a comprehensive signal evaluation system and method to determine the signal transmission parameters of multiple comprehensive signal analyzers during joint simulation analysis, and to improve the evaluation accuracy of the simulation analysis effect of the comprehensive signal analyzer. SUMMARY

[0004] One of the embodiments of the present specification provides a comprehensive signal evaluation system, the system includes at least one comprehensive signal analyzer and a remote terminal; the comprehensive signal analyzer includes a communication module, a signal generation module, a spectrum analysis module, an index test module, a map location module, and an analysis and training module; the communication module is configured to transmit data with the signal generation module, the spectrum analysis module, the index test module, the map location module, and the analysis and training module; the signal generation module includes a parameter submodule and a transmission submodule; the signal generation module is configured to: based on the transmission parameters, generate and transmit a first signal and / or generate and transmit a second signal through the transmission submodule; the transmission The parameters include the transmission order of multiple first signals, the transmission order of multiple second signals, the frequency, duration and number of transmissions; the parameter submodule is configured to generate and transmit the first signal, the first signal includes a frequency modulation signal, an amplitude modulation signal, a pulse signal, a swept frequency signal and at least one type of first digital modulation signal; the transmission submodule is configured to generate and transmit the second signal, the second signal includes at least one of an analog modulation signal, a second digital modulation signal, a digital intercom signal, a digital transmission cheating signal, a cellular communication signal and a radar signal; the spectrum analysis module is configured to: obtain a user analysis operation, execute the user analysis operation and return the user analysis result; the user analysis operation It includes at least one of frequency sweep, channel power measurement, occupied bandwidth measurement, time domain measurement, analog demodulation, voice demodulation, digital demodulation, IQ data acquisition and playback; the index test module is configured to: obtain user test operations, execute the user test operations and return test results; the user test operations include semi-automatic testing of test items; the test items are at least one of monitoring sensitivity, level measurement error, frequency stability monitoring, scanning speed monitoring and receiver spurious; the map location module is configured to: provide the device location information and user information of the integrated signal analyzer; the user information includes the punch-in person and / or punch-in time of the integrated signal analyzer; the analysis and training module includes learning sub module and a training submodule; the learning submodule is configured to: push learning content to the user based on the learning content library; the training submodule is configured to: obtain training signal data based on user configuration parameters, and generate test questions based on the training signal data; in response to obtaining the user analysis results, upload the user analysis results to the remote terminal; the remote terminal is configured to: obtain the device location information and user information of the integrated signal analyzer through the map location module; determine simulation test parameters based on the device location information and the user information, and send the simulation test parameters to the integrated signal analyzer; the simulation test parameters include the transmission parameters of the integrated signal analyzer;In response to obtaining the user analysis result of the integrated signal analyzer, determining a simulation test result based on the user analysis result; the simulation test result includes a user test score of the user.

[0005] One of the embodiments of this specification provides a comprehensive signal evaluation method, which includes: obtaining device location information and user information of a comprehensive signal analyzer through a map location module; determining simulation test parameters based on the device location information and the user information, and sending the simulation test parameters to the comprehensive signal analyzer; the simulation test parameters include transmission parameters of the comprehensive signal analyzer; in response to obtaining a user analysis result of the comprehensive signal analyzer, determining a simulation test result based on the user analysis result; the simulation test result includes a user test score of the user.

[0006] One of the embodiments of this specification provides a comprehensive signal evaluation device, which includes at least one processor and at least one memory; the at least one memory is used to store computer instructions; and the at least one processor is used to execute at least part of the computer instructions to implement the aforementioned comprehensive signal evaluation method.

[0007] One embodiment of this specification provides a computer-readable storage medium, wherein the storage medium stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the aforementioned integrated signal evaluation method. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] This specification will be further described in the form of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting, and in these embodiments, like numbers represent like structures, wherein:

[0009] Figure 1 is an exemplary module diagram of a comprehensive signal evaluation system according to some embodiments of this specification;

[0010] Figure 2 is an exemplary flow chart of a comprehensive signal evaluation method according to some embodiments of this specification;

[0011] Figure 3 is an exemplary schematic diagram of determining simulation test parameters according to some embodiments of this specification;

[0012] Figure 4 is an exemplary schematic diagram of a determination model according to some embodiments of this specification;

[0013] Figure 5 This is an exemplary flowchart for determining first fault information and second fault information according to some embodiments of this specification. DETAILED DESCRIPTION

[0014] In order to more clearly illustrate the technical solutions of the embodiments of the present specification, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some examples or embodiments of the present specification, and for those skilled in the art, the present specification can also be applied to other similar scenarios without creative labor on the basis of these drawings. Unless it is clear from the language environment or otherwise stated, the same reference numbers in the drawings represent the same structures or operations.

[0015] It should be understood that the "system", "device", "unit" and / or "module" used herein is a method for distinguishing different components, elements, parts, sections or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

[0016] As shown in the specification and claims, unless the context clearly indicates otherwise, the words "one", "a", "an", and / or "the" do not refer to the singular, but can also include the plural. Generally, the terms "comprise" and "include" only indicate the inclusion of the steps and elements explicitly identified, and these steps and elements do not constitute an exclusive list of methods or devices.

[0017] Flowcharts are used in the present specification to illustrate the operations performed by the system according to the embodiments of the present specification. It should be understood that the preceding or subsequent operations are not necessarily performed in sequence. On the contrary, each step can be processed in reverse order or simultaneously. At the same time, other operations can be added to these processes, or one or more steps of the operation can be removed from these processes.

[0018] Figure 1 is an exemplary module diagram of the comprehensive signal evaluation system according to some embodiments of the present specification. The comprehensive signal evaluation system according to the embodiments of the present specification will be described in detail below. It should be noted that the following embodiments are only used to explain the present specification and do not constitute a limitation on the present specification.

[0019] In some embodiments, as shown in Figure 1 The comprehensive signal evaluation system 100 can include at least one comprehensive signal analyzer 110, a remote terminal 120 and a management terminal 130. The comprehensive signal analyzer 110 can include a communication module 111, a signal generation module 112, a spectrum analysis module 113, an index test module 114, a map location module 115 and an analysis training module 116. The signal generation module 112 includes a parameter sub-module 112-1 and a transmission sub-module 112-2, and the analysis training module 116 includes a learning sub-module 116-1 and a training sub-module 116-2.

[0020] The integrated signal analyzer 110 is a device that integrates various signal generation methods, spectrum analysis and measurement, signal analysis training, interference source detection, and receiver performance testing. In some embodiments, the integrated signal analyzer 110 includes a communication module 111, a signal generation module 112, a spectrum analysis module 113, a performance testing module 114, a map location module 115, and an analysis and training module 116.

[0021] In some embodiments, different integrated signal analyzers may have different functions. For example, integrated signal analyzer A may only transmit signals. Integrated signal analyzer B may only receive and analyze signals. Integrated signal analyzer C may both transmit and receive signals and analyze them.

[0022] The communication module 111 is a module for implementing data transmission and communication functions. For example, the communication module 111 may include but is not limited to a communication interface, a protocol stack, and the like.

[0023] In some embodiments, the communication module 111 can perform data transmission with the signal generation module 112 , the spectrum analysis module 113 , the index testing module 114 , the map location module 115 and the analysis and training module 116 .

[0024] The signal generation module 112 is a module for generating and transmitting a signal. In some embodiments, the signal generation module 112 includes a parameter submodule 112-1 and a transmission submodule 112-2.

[0025] The parameter submodule 112 - 1 is a module that can generate and transmit a custom signal. In some embodiments, the parameter submodule 112 - 1 can generate and transmit a first signal.

[0026] The first signal refers to a signal generated and transmitted by the parameter submodule. In some embodiments, the first signal may include but is not limited to a frequency modulation signal, an amplitude modulation signal, a pulse signal, a swept frequency signal, and at least one type of first digital modulation signal.

[0027] A digitally modulated signal is a signal that converts digital data into a signal suitable for transmission over a communication channel. For example, digitally modulated signals may include, but are not limited to, binary phase shift keying (BPSK), differentially coherent binary phase shift keying (DBPSK), quadrature phase shift keying (QPSK), and 8-phase shift keying (8PSK).

[0028] In some embodiments, the digital modulated signal can include a first digital modulated signal and a second digital modulated signal. Wherein the first digital modulated signal refers to the digital modulated signal generated and transmitted by the parameter submodule.

[0029] The transmission submodule 112-2 refers to a module capable of supporting the single or cyclic transmission of multiple signals according to the user-defined order, frequency, and duration. In some embodiments, the transmission submodule 112-2 can include a rich signal waveform file library.

[0030] The signal waveform file library refers to a database composed of multiple signal waveform files. For example, the signal waveform file library can include but is not limited to the second signal, etc.

[0031] The second signal refers to the service signal generated and transmitted by the transmission submodule. In some embodiments, the second signal can include but is not limited to analog modulated signals, second digital modulated signals, digital talkback signals, data transmission cheating signals, cellular communication signals, radar signals, and other common service signals. Wherein the service signal refers to a signal used to transmit service data.

[0032] The second digital modulated signal is similar to the first digital modulated signal, the difference is that the second digital modulated signal is generated and transmitted by the transmission submodule.

[0033] In some embodiments, the signal generation module 112 is configured to generate and transmit the first signal through the parameter submodule 112-1 and / or the second signal through the transmission submodule 112-2 based on the transmission parameters. For example, the signal generation module 112 can generate and transmit the first signal through the parameter submodule 112-1 and / or the second signal through the transmission submodule 112-2 based on the frequency in the transmission parameters according to the lookup table. For example only, in response to the frequency of signal A being in the interval [x1, x2], signal A is determined as the first signal and transmitted through the parameter submodule; in response to the frequency of signal B being in the interval [x3, x4], signal B is determined as the second signal and transmitted through the transmission submodule, etc., without limitation.

[0034] The lookup table refers to a table used to map the relationship between the transmission parameters and the corresponding submodules (i.e., parameter submodule, transmission submodule) in the signal generation module. In some embodiments, the lookup table can correspond the transmission parameters to two submodules of the signal parameter module, so that the comprehensive signal evaluation system can accurately generate and transmit the first signal through the parameter submodule and / or the second signal through the transmission submodule.

[0035] Transmission parameters refer to parameters related to signal transmission. For example, transmission parameters may include but are not limited to the transmission order of multiple first signals, the transmission order of multiple second signals, frequency, duration, and number of transmissions.

[0036] A frequency point refers to a number or name used to identify and distinguish a specific frequency in radio communications or signal processing. In some embodiments, each frequency point corresponds to a fixed frequency value.

[0037] In some embodiments, the remote terminal may determine the transmission parameters in a variety of ways. For example, the remote terminal may determine the transmission parameters corresponding to the first signal and the second signal by querying a first preset relationship table based on the first signal and the second signal.

[0038] In some embodiments, the first preset relationship table may include a correspondence between the first signal, the second signal, and the transmission parameters. In some embodiments, the first preset relationship table may be determined based on the first signal, the second signal, and the actual transmission parameters in historical data.

[0039] The spectrum analysis module 113 is a module used to obtain user analysis operations, execute user analysis operations and return user analysis results.

[0040] User analysis operations refer to the operations involved in executing specific analysis tasks by entering commands or parameters through the integrated signal analyzer's interface. In some embodiments, user analysis operations may include, but are not limited to, frequency sweeping, measuring channel power, measuring occupied bandwidth, time domain measurements, analog demodulation, voice demodulation, digital demodulation, IQ data acquisition and playback, and more. Frequency sweeping may include, but is not limited to, shortcut functions such as background signal acquisition, automatic signal discovery, peak signal search, one-click software screenshots, and marker difference calculation.

[0041] For more information about user analysis results, see Figure 2 and its related descriptions.

[0042] The indicator testing module 114 is a module that obtains user testing operations, executes user testing operations and returns test results.

[0043] In some embodiments, the indicator testing module 114 may also support viewing of test history records, resuming testing from breakpoints, and generating a test report with one click after the test is completed.

[0044] User test operations refer to operations involved in executing specific test tasks by inputting instructions or parameters through the interface of the integrated signal analyzer. In some embodiments, user test operations may include but are not limited to semi-automatic testing of test items.

[0045] Test items refer to the items to be tested. For example, test items may include but are not limited to monitoring sensitivity, level measurement error, frequency stability monitoring, scanning speed monitoring, and receiver spurious detection.

[0046] The test result is the result returned after the user performs the user test operation. For example, the test result can be expressed as a numerical value, where the higher the numerical value, the better the test result.

[0047] The map location module 115 is a module for providing device location information and user information of the integrated signal analyzer.

[0048] For information about device location information and user information, please refer to Figure 2 and its related descriptions.

[0049] In some embodiments, the signal source can be used as an interference source in the interference search project of the radio technology exercise to find and locate the interference source. The map location module 115 can display the current latitude and longitude information of the integrated signal analyzer. In response to the integrated signal analyzer turning on the remote service, the punch-in function can report the information of the punch-in user to the remote terminal. The remote terminal can receive real-time information such as the punch-in personnel, punch-in time, geographic location, etc. of multiple integrated signal analyzers under control, and remotely control the transmission of the signal source accordingly.

[0050] The analysis and training module is a module that provides learning content and performs tests for users. In some embodiments, the analysis and training module 116 includes a learning submodule 116 - 1 and a training submodule 116 - 2 .

[0051] The learning submodule 116-1 refers to a module that provides learning knowledge points to users. In some embodiments, the learning submodule 116-1 is configured to push learning content to users based on a learning content library. The learning content library includes a wealth of learning resources, for example, covering analog modulation signals, digital modulation signals, pulse modulation signals, frequency sweep signals, digital intercom signals, digital transmission cheating signals, and cellular communication signals, as well as selecting some typical signals from the aforementioned major categories of signals and making a signal feature library. The signal feature library contains information such as the frequency domain, time domain characteristics, spectrum diagram, time domain diagram, IQ diagram, constellation diagram, modulation mode, and symbol rate of the signal. A demonstration video of signal analysis is also provided for individual signals.

[0052] The training submodule 116-2 is a module that provides test questions for users to test. In some embodiments, the training submodule is configured to obtain training signal data based on user-configured parameters, generate test questions based on the training signal data, and upload the user analysis results to the remote terminal 120 in response to obtaining the user analysis results.

[0053] In some embodiments, the training guidance step of the training submodule 116-2 can guide the user through a complete process of signal generation and analysis, obtain user analysis results, and finally provide the user analysis results to the remote terminal. Detailed operation methods and user configuration parameters are provided in the steps.

[0054] User-configured parameters refer to parameters related to the signal received by the integrated signal analyzer that the user adjusts. For example, user-configured parameters may include, but are not limited to, the frequency range and bandwidth of the signal, etc., which are not limited here.

[0055] In some embodiments, user configuration parameters may be set by professional technicians or by system defaults.

[0056] The training signal data refers to a data set used to train the integrated signal analyzer. For example, the training signal data may include, but is not limited to, various types of signals and their parameters (eg, modulation type, frequency, amplitude, phase, etc.).

[0057] In some embodiments, the training submodule 116 - 2 may use the signal data received through the user testing operation as the training signal data.

[0058] Test questions refer to questions used to test users.

[0059] In some embodiments, the training submodule may convert the training signal data into data that can be recognized by the machine and easily transmitted, and then serve as test questions.

[0060] The remote terminal 120 refers to a hardware device used to interact with and perform operations on the integrated signal analyzer 110. For example, the remote terminal may include any one of a mobile device, tablet computer, laptop computer, desktop computer, or any combination thereof, with input and / or output capabilities. In some embodiments, the remote terminal 120 may also include input devices, output devices, and the like. Input devices may include a keyboard, touch screen, voice control device, or any combination thereof. Output devices may include a display, speaker, printer, or any combination thereof. In some embodiments, the remote terminal may also include a processor.

[0061] In some embodiments, the remote terminal 120 is configured to obtain the device location information and user information of the integrated signal analyzer through the map location module 115; determine the simulation test parameters based on the device location information and user information, and send the simulation test parameters to the integrated signal analyzer; in response to the user analysis results obtained from the integrated signal analyzer, determine the simulation test results based on the user analysis results. For details about this embodiment, please refer to Figure 2 and its related descriptions.

[0062] In some embodiments, the remote terminal 120 is further configured to determine the grouping information of the integrated signal analyzer based on the device location information and user information of the integrated signal analyzer; and determine the simulation test parameters based on the grouping information of the integrated signal analyzer. Figure 3 and its related descriptions.

[0063] In some embodiments, the remote terminal 120 is further configured to determine the evaluation difficulty based on the device location information and user information of the integrated signal analyzer; and determine the grouping information of the integrated signal analyzer based on the evaluation difficulty. Figure 3 and its related descriptions.

[0064] In some embodiments, the remote terminal 120 is further configured to determine candidate test parameters; determine analysis difficulty based on the candidate test parameters; and determine simulation test parameters based on the analysis difficulty. Figure 3 and its related descriptions.

[0065] In some embodiments, the remote terminal 120 is further configured to determine candidate test parameters based on the user's historical user test scores and historical test parameters. Figure 3 and its related descriptions.

[0066] In some embodiments, the remote terminal 120 is further configured to determine the analysis difficulty by determining the model based on the device location information, user information, and candidate test parameters of the integrated signal analyzer. Figure 4 and its related descriptions.

[0067] In some embodiments, the remote terminal 120 is further configured to determine the user test score of the user based on the user analysis result of the integrated signal analyzer; and determine the first fault information based on the user test score of the user. Figure 5 and its related descriptions.

[0068] In some embodiments, the remote terminal 120 is further configured to determine an abnormal value of the integrated signal analyzer based on the user test score of the user; determine first fault information through a judgment model based on the abnormal value and the latest maintenance result of the integrated signal analyzer; in response to determining that the integrated signal analyzer has a fault based on the first fault information, generate a maintenance instruction and send it to the management terminal; in response to obtaining the maintenance result from the management terminal, determine second fault information of the integrated signal analyzer based on the maintenance result. For details about this embodiment, please refer to Figure 5 and its related descriptions.

[0069] In some embodiments, the remote terminal 120 is further configured to restart the test on the integrated signal analyzer in response to the inspection result meeting the preset condition. Figure 5 and its related descriptions.

[0070] The management terminal 130 refers to a component for receiving, processing, and distributing various messages. For example, the management terminal may include but is not limited to a cloud platform, an application, and the like.

[0071] In some embodiments, the management terminal 130 is configured to push the maintenance instructions to the administrator and obtain the maintenance results. For details about the maintenance instructions and maintenance results, please refer to Figure 5 and its related descriptions.

[0072] It should be noted that the above description of the system and platform is for convenience only and does not limit this specification to the scope of the embodiments described. It is understood that those skilled in the art, after understanding the principles of the system, may arbitrarily combine the modules or form subsystems connected to other modules without departing from these principles.

[0073] Figure 2 FIG. 1 is an exemplary flow chart of a comprehensive signal evaluation method according to some embodiments of this specification. Figure 2 As shown, the process 200 includes the following steps: In some embodiments, the process 200 may be executed by the remote terminal 120 in the integrated signal evaluation system 100 .

[0074] In some embodiments, the remote terminal can obtain the device location information and user information of the integrated signal analyzer through the map location module; determine the simulation test parameters based on the device location information and user information, and send the simulation test parameters to the integrated signal analyzer; in response to the user analysis results obtained from the integrated signal analyzer, determine the simulation test results based on the user analysis results.

[0075] For information about remote terminals, map location modules, and integrated signal analyzers, see Figure 1 and its related descriptions.

[0076] Step 210: Obtain device location information and user information of the integrated signal analyzer through a map location module.

[0077] The device location information refers to the current location of the integrated signal analyzer. For example, the device location information may be the latitude and longitude information of the integrated signal analyzer.

[0078] In some embodiments, the remote terminal may obtain the device location information of the integrated signal analyzer through components such as a GPS receiver and Bluetooth in the map location module.

[0079] The user information refers to information of a user using the comprehensive signal analyzer. For example, the user information can include, but is not limited to, a clock-in person of the comprehensive signal analyzer, a clock-in time, and the like.

[0080] In some embodiments, the remote terminal can obtain, through an application in the map location module (for example, an application for user login clock-in, and the like), a user using the comprehensive signal analyzer and a clock-in time of the user.

[0081] In step 220, simulation test parameters are determined based on the device location information and the user information, and the simulation test parameters are sent to the comprehensive signal analyzer.

[0082] The simulation test parameters refer to parameters for configuring and adjusting a signal-emitting device (for example, the comprehensive signal analyzer for emitting signals) when performing signal simulation tests. For example, the simulation test parameters can include, but are not limited to, emission parameters of at least one comprehensive signal analyzer.

[0083] In some embodiments, the remote terminal can determine test questions from a test question library based on the device location information and the user information, and use simulation test parameters corresponding to the test questions as the simulation test parameters. For example, the remote terminal can construct a feature vector based on the device location information and the user information, and perform a search in a vector database based on the feature vector to determine the test questions.

[0084] The test question library refers to a database for storing multiple sets of test questions and related information. In some embodiments, the test question library can include multiple sets of device location information, user information, and corresponding test questions that need to be tested.

[0085] In some embodiments, the test question library can be pre-set by professional technicians or the system.

[0086] In some embodiments, the test question library can also be implemented based on a vector database.

[0087] The vector database refers to a database for determining test questions. In some embodiments, the vector database contains multiple reference vectors and reference test questions corresponding to each reference vector.

[0088] In some embodiments, the remote terminal can construct a reference vector based on corresponding historical device location information and historical user information in historical data, and use actual test questions in the historical data as the reference test questions. The actual test questions in the historical data can be determined by the remote terminal or the user based on prior experience.

[0089] In some embodiments, the remote terminal can calculate the similarity between the reference vector and the feature vector respectively, and determine the test question corresponding to the feature vector. For example, a reference vector whose similarity with the feature vector meets a preset condition is used as the target vector, and the reference test question corresponding to the target vector is used as the test question corresponding to the feature vector. The preset condition can be determined according to the situation. For example, the preset condition can be that the similarity is greater than a preset similarity threshold. The similarity between the reference vector and the feature vector can be negatively correlated with the vector distance between the reference vector and the feature vector, and the vector distance can be determined based on cosine distance, etc. For example, the similarity can be the inverse of the vector distance.

[0090] For more information about the test questions, see Figure 1 and its related descriptions.

[0091] For other embodiments of determining simulation test parameters based on device location information and user information of the integrated signal analyzer, please refer to Figure 3 and its related descriptions.

[0092] Step 230 : In response to obtaining the user analysis result of the integrated signal analyzer, determining a simulation test result based on the user analysis result.

[0093] User analysis results refer to data on signal-related parameters analyzed by the user. For example, user analysis results may include but are not limited to the type and period of the signal.

[0094] The signal type is used to classify the type of signal generated, for example, digital signal, analog signal, etc.

[0095] The period of a signal is used to measure the periodic characteristics of the signal.

[0096] The simulation test result refers to the performance data obtained after the user takes the test. For example, the simulation test result may include but is not limited to the user's user test score.

[0097] The user test score is an indicator used to quantify the user's performance in the test. For example, a higher user test score indicates that the user performed better in the test, which means the simulation test results are better.

[0098] In some embodiments, each time a user takes a test, the remote terminal may obtain a user test score corresponding to the user in the test.

[0099] In some embodiments, the remote terminal may use the average of all user test scores of the user in the historical data as the user test score.

[0100] In some embodiments, the remote terminal may further determine the user test score based on the analysis difficulty and the evaluation difficulty using a first preset rule. For example, the first preset rule may be that the higher the average value of the analysis difficulty and the average value of the evaluation difficulty, the higher the user test score.

[0101] For more information on analysis difficulty and assessment difficulty, please refer to the following Figure 3 and its related descriptions.

[0102] In some embodiments, the harder the test questions are, the harder it is to score. In order to enable longitudinal comparison of user test scores, that is, to compare different tests (e.g., this test and the previous test), it is important to consider the difficulty of the test questions.

[0103] In some embodiments of the present specification, by considering the difficulty of the test questions, the user test scores of users can be compared longitudinally, thereby more fairly evaluating the actual abilities of users and ensuring that the user test scores of users can reflect their actual levels.

[0104] In some embodiments, the remote terminal may compare the user analysis results of the integrated signal analyzer with all the transmission parameters of the integrated signal analyzer to obtain a user test score for the user. For example, based on the user analysis results of the integrated signal analyzer, the remote terminal may determine a simulation test score by comparing the analyzed signal-related parameters (e.g., frequency, signal type) with the transmission parameters of the integrated signal analyzer.

[0105] For example only, for each signal parameter (hereinafter referred to as a sub-question) to be analyzed, if the user's analysis result is consistent with the transmission parameter, it is considered correct; if it is inconsistent, it is considered incorrect. Ultimately, the user's user test score is calculated by dividing the number of correct sub-questions by the total number of sub-questions, expressing the user's test accuracy as a percentage. For example, if a user correctly answers 4 out of 10 sub-questions in the frequency comparison and 3 out of 10 in the signal type comparison, the user's user test score is 70%.

[0106] In some embodiments of this specification, a comprehensive signal analyzer can include multiple functions, covering commonly used functions, and can also provide automated customized learning content to help users learn signal analysis. By providing users with different skill levels with signal analysis simulation tests, users' skills can be further improved.

[0107] It should be noted that the above description of process 200 is for illustration and purpose only and does not limit the scope of application of this specification. Those skilled in the art may make various modifications and variations to process 200 under the guidance of this specification. However, such modifications and variations are still within the scope of this specification.

[0108] Figure 3 FIG. 1 is an exemplary diagram of determining simulation test parameters according to some embodiments of this specification. Figure 3 As shown, determining simulation test parameters based on the device location information and user information of the integrated signal analyzer may include the following: In some embodiments, determining simulation test parameters based on the device location information and user information of the integrated signal analyzer may be performed by a remote terminal.

[0109] In some embodiments, the remote terminal may determine the grouping information 330 of the integrated signal analyzer based on the device location information 310 and user information 320 of the integrated signal analyzer; and determine the simulation test parameters 340 based on the grouping information 330 of the integrated signal analyzer.

[0110] For more information about device location information, user information, and simulation test parameters, see Figure 2 and its related descriptions.

[0111] Grouping refers to the organization of information by functionally classifying participating integrated signal analyzers during signal analysis or communications testing. For example, grouping can include, but is not limited to, transmit groups, receive groups, and interference groups.

[0112] The transmitting group consists of at least one integrated signal analyzer, which is responsible for transmitting one of the non-interfering signals in the (composite) signal that the user needs to analyze.

[0113] The receiving group also includes at least one integrated signal analyzer, whose function is to receive signals. In some embodiments, the transmitting and receiving signals can be performed by the same integrated signal analyzer. In some embodiments, to prevent interference from the transmitting signal to the receiving side, different integrated signal analyzers can be used for the transmitting and receiving signals. The specific configuration is determined by professional technicians and is not limited here.

[0114] The interference group also includes at least one integrated signal analyzer specifically for transmitting interference signals. Similar to the receiving group, in some embodiments, to prevent interference from the transmitted interference signal on the receiving end, the integrated signal analyzers for transmitting the interference signal and receiving the signal can typically be different. However, in some cases, they can be the same integrated signal analyzer. The specific configuration is determined by professional technicians and is not a limitation here.

[0115] In some embodiments, the remote terminal can take the comprehensive signal analyzers logged in by the user as the receiving group in the grouping information; select a preset number of comprehensive signal analyzers from the plurality of comprehensive signal analyzers not logged in by the user as the transmitting group according to a second preset rule; and take the remaining comprehensive signal analyzers as the interference group.

[0116] The second preset rule refers to a set of pre-set selection criteria or principles formulated in signal analysis or communication testing in order to form the transmitting group. These rules are used to guide how to select a preset number of comprehensive signal analyzers from the plurality of comprehensive signal analyzers not logged in by the user to form the transmitting group. In some embodiments, the specific content of the second preset rule can be pre-set by professional technicians or the system according to testing requirements and the like. For example, the second preset rule can be to select comprehensive signal analyzers that are not adjacent as the transmitting group. The non-adjacent can refer to non-adjacent in the physical position of the comprehensive signal analyzers, or non-adjacent in signal frequency allocation, and the like, which is not limited herein.

[0117] The preset number refers to the number of comprehensive signal analyzers in the transmitting group determined on the basis of the second preset rule.

[0118] In some embodiments, the preset number can be set by default by professional technicians or the system.

[0119] In some embodiments, the grouping information can further include adjacent information between the comprehensive signal analyzers. Figure 3 is an exemplary schematic diagram of determining analog test parameters according to some embodiments of the present specification. As shown in Figure 3 , the remote terminal can determine the evaluation difficulty 350 based on the device location information 310 and the user information 320 of the comprehensive signal analyzers, and determine the grouping information 330 of the comprehensive signal analyzers based on the evaluation difficulty 350.

[0120] For more information about the device location information and the user information, please refer to Figure 2 and the related description thereof.

[0121] The adjacent information refers to the information of the comprehensive signal analyzers that are physically adjacent within each group (e.g., the transmitting group, the receiving group, and the interference group) of the grouping information. For example, the comprehensive signal analyzer 1 and the comprehensive signal analyzer 3 in the transmitting group are physically adjacent.

[0122] Difficulty assessment involves evaluating the ability levels of test participants and determining the test difficulty level they can accept. For example, difficulty assessment can be expressed numerically, with increasing numerical values ​​representing increasing difficulty. Difficulty assessment is typically graded in a stepped manner, with each level corresponding to a different level of difficulty. For example, difficulty assessment is divided into several levels, each with a clear numerical representation. For example, if there are three levels, 1 might represent easy difficulty, 2 might represent medium difficulty, and 3 might represent hard difficulty.

[0123] In some embodiments, the evaluation difficulty should match the user's knowledge level, experience, etc., and the evaluation difficulty may be different for different users. As an example only, the higher the user's knowledge level and the more experienced they are, the higher the evaluation difficulty for that user.

[0124] In some embodiments, the remote terminal can determine the assessment difficulty using various methods based on device location information and user information. For example, the remote terminal can query historical data for the user test scores corresponding to each integrated signal analyzer that the user has logged into, and then determine the assessment difficulty for the user by taking the average of the user test scores of all the integrated signal analyzers logged into by querying a second preset relationship table.

[0125] In some embodiments, the second preset relationship table may include a correspondence between the average user test scores and the assessment difficulty. For example, the higher the average user test scores corresponding to a user, the higher the assessment difficulty. In some embodiments, the second preset relationship table may be determined based on the user test scores in historical data and the actual assessment difficulty.

[0126] In some embodiments, based on the aforementioned determined grouping information, the remote terminal may, in response to a higher evaluation difficulty, increase the number of integrated signal analyzers in the interference group and increase the number of physically adjacent integrated signal analyzers in the transmission group.

[0127] In some embodiments of this specification, the difficulty of the test questions can be effectively increased by increasing the number of integrated signal analyzers in the interference group and clustering the integrated signal analyzers in the transmission group more closely (i.e., increasing the number of integrated signal analyzers in physically adjacent locations). This is because the more integrated signal analyzers in the interference group, the more complex the steps of separating and analyzing the received signals will become, requiring a higher level of skill and more processing time. At the same time, the more clustered the integrated signal analyzers in the transmission group, the more likely it is that the transmitted signals will produce a superposition effect, which increases the difficulty of signal reception and identification, making the test more challenging.

[0128] In some embodiments, the grouping information is also related to the difficulty of analysis of the candidate test parameters.

[0129] Candidate test parameters refer to a set of parameters that can be used as simulation test parameters.

[0130] For more information about simulation test parameters, see Figure 2 and its related descriptions.

[0131] In some embodiments, the remote terminal may sort the usage frequencies of simulation test parameters from the historical simulation test records from high to low, and select a preset number of simulation test parameters with the highest rankings as candidate test parameters.

[0132] The preset number can be pre-set by professional technicians or the system. In some embodiments, the preset number can be adjusted according to the computing resources of the processor in the remote terminal, but cannot be increased indefinitely under the response time limit. For example, if the response is required to be completed within 0.1 seconds, and the amount of calculation that can be processed within 0.1 seconds is between a and b under the current computing resources, and the amount of calculation to calculate a candidate test parameter is x, then the value of the preset number should meet a <N*x<b的条件,以确保在规定的响应时间内完成候选测试参数的计算和筛选。其中,N为预设数量的取值。

[0133] In some embodiments, the remote terminal may also determine candidate simulation test parameters based on the user's historical test scores and historical test parameters.

[0134] Historical test scores refer to the user test scores of users in historical data. For more information about user test scores, see Figure 2 and its related descriptions.

[0135] Historical test parameters refer to the corresponding simulation test parameters in historical data. For more information about simulation test parameters, see Figure 1 、 Figure 2 and its related descriptions.

[0136] In some embodiments, the remote terminal can determine simulation test parameters in a variety of ways based on historical test scores and historical test parameters. For example, the remote terminal can collect fluctuation data of the user's historical test scores under various historical test parameters, as well as the number of occurrences of each historical test parameter. Historical test parameters whose fluctuation data within a recent preset historical time period is less than a fluctuation threshold, and whose number of occurrences is greater than a frequency threshold, are selected as candidate test parameters.

[0137] The recent historical preset time period refers to a period of historical time close to the current moment, for example, the last week, the last month, etc., which is not limited here and can be set by professional technicians or system defaults.

[0138] Fluctuation data refers to the data obtained by dividing the standard deviation of historical test scores by the mean.

[0139] In some embodiments, the remote terminal may accumulate the number of times each historical test parameter appears within a recent historical preset time period, and use this as the number of times the historical test parameter appears.

[0140] The frequency threshold refers to a threshold used to determine whether the usage frequency of each historical test parameter in the historical data is high enough.

[0141] In some embodiments, the frequency threshold may be set by a professional technician or by system default.

[0142] In some embodiments, the remote terminal may further determine the frequency threshold based on the number of candidate test parameters using a third preset rule. As an example only, the third preset rule may be that the fewer the number of candidate test parameters, the higher the frequency threshold.

[0143] In some embodiments, in response to the smaller number of candidate test parameters, setting the frequency threshold higher can indicate that users may be more inclined to use test questions that are more representative, more frequently used, and less likely to make mistakes. Test questions that are used less frequently may be biased or unreasonable in themselves, and these test questions may not be selected again or will be replaced by new test questions. Therefore, test questions that are used more frequently tend to be more complete, less prone to errors, and can effectively perform their testing functions.

[0144] Fluctuation threshold refers to the threshold used to determine whether historical test scores are stable.

[0145] In some embodiments, the fluctuation threshold may be set by a professional technician or by system default.

[0146] In some embodiments, the remote terminal may further determine the fluctuation threshold value based on the fluctuation data of the historical test scores of the users participating in the test by a fourth preset rule. As an example only, the fourth preset rule may be that the greater the fluctuation data of the historical test scores, the higher the fluctuation threshold value.

[0147] In some embodiments, the greater the fluctuation data of the historical test scores of the users participating in the test, the higher the fluctuation threshold should be set accordingly. This is because when the levels of users vary greatly, questions that can test the differences among users should be selected.

[0148] In some embodiments of this specification, the historical performance of simulation test parameters is evaluated by considering the user's historical test scores and historical test parameters, thereby selecting appropriate candidate test parameters, so that the subsequently obtained simulation test parameters can better meet the requirements.

[0149] Analyzing difficulty refers to analyzing the difficulty of a test question based on candidate test parameters. For example, analytical difficulty can be expressed as a numerical value, where a higher numerical value indicates greater analytical difficulty.

[0150] In some embodiments, the analysis difficulty needs to match the assessment difficulty. For example, if the assessment difficulty has three levels, 1 for easy, 2 for medium, and 3 for hard, the analysis difficulty should also be divided into three levels, with the difficulty of each level consistent with the assessment difficulty.

[0151] In some embodiments, the analysis difficulty is independent of how different users analyze, and can be used to represent the difficulty of a test question.

[0152] For more information about the test questions, see Figure 1 and its related descriptions; for the content of assessment difficulty, please refer to Figure 3 and its related descriptions.

[0153] In some embodiments, the remote terminal may count the user test scores of all users under the simulation test parameters in all test records, and use the average of the user test scores of the aforementioned multiple users as the analysis difficulty.

[0154] In some embodiments, the remote terminal may calculate the mean of the analysis difficulty of all candidate test parameters (hereinafter referred to as the analysis difficulty mean). When the aforementioned analysis difficulty mean is different from the evaluation difficulty (or the absolute value of the difference between the analysis difficulty mean and the evaluation difficulty is greater than the error threshold), in response to the analysis difficulty being less than the evaluation difficulty, the number of integrated signal analyzers in the interference group is further increased, and the number of physically adjacent integrated signal analyzers in the transmission group is further increased; in response to the analysis difficulty being greater than or equal to the evaluation difficulty, the number of integrated signal analyzers in the interference group is reduced, and the number of physically adjacent integrated signal analyzers in the transmission group is reduced.

[0155] The error threshold refers to a threshold used to determine whether the difference between the mean analysis difficulty and the evaluation difficulty is large enough. In some embodiments, the error threshold can be set by professional technicians or by system default.

[0156] In some embodiments of this specification, grouping integrated signal analyzers can determine the difficulty of received test questions to a certain extent. If the difficulty of the test questions generated by subsequent evaluation is insufficient or exceeds the initially set evaluation difficulty, the difficulty of the test questions can be adjusted by adjusting the grouping information.

[0157] In some embodiments, the remote terminal may use the transmission parameters in the transmission group and the interference group as simulation test parameters. In some embodiments, in response to the integrated signal analyzer being the transmission group, the remote terminal may randomly generate a signal for each integrated signal analyzer in the transmission group, and use the parameters of the signal as the transmission parameters of the integrated signal analyzer. As an example only, the remote terminal may randomly select a digital modulation signal from the first signal transmitted by the parameter submodule, and / or randomly select a service signal from the second signal transmitted by the transmission submodule, and use the aforementioned randomly selected modulation signal and / or service signal as the transmission parameters of the integrated signal analyzer. In response to the integrated signal analyzer being the interference group, the remote terminal may randomly generate a noise, and use the parameters of the noise as the transmission parameters of the integrated signal analyzer.

[0158] In some embodiments, the remote terminal may further determine candidate test parameters, determine analysis difficulty based on the candidate test parameters, and determine simulation test parameters based on the analysis difficulty. For example, the remote terminal may select simulation test parameters corresponding to the analysis difficulty that is closest to the assessment difficulty as the simulation test parameters.

[0159] The analysis difficulty closest to the evaluation difficulty may be the one with the smallest numerical difference between the evaluation difficulty and the analysis difficulty, and there is no limitation on this.

[0160] For more information on candidate test parameters, assessment difficulty, and analysis difficulty, see Figure 3 Related description in the previous article.

[0161] In some embodiments of the present specification, by evaluating the difficulty of candidate test parameters and selecting simulation test parameters that are closest to the level of the user currently taking the test, the purpose of teaching students in accordance with their aptitude can be achieved.

[0162] In some embodiments of this specification, by grouping integrated signal analyzers and clarifying the transmission parameters of each integrated signal analyzer, the signal quality can be ensured during the signal generation stage, thereby effectively preventing the quality of test items from being reduced due to signal problems.

[0163] Figure 4 is an exemplary schematic diagram of a determination model according to some embodiments of this specification.

[0164] In some embodiments, as Figure 4 As shown, the remote terminal may determine the analysis difficulty 430 by determining a model 420 based on the device location information 310 of the integrated signal analyzer, the user information 320 , and the candidate test parameters 410 .

[0165] For information about device location information and user information, please refer to Figure 2 and its related descriptions; for details on candidate test parameters and analysis difficulty, please refer to Figure 3 and its related descriptions.

[0166] The determination model refers to a model used to determine the difficulty of the analysis. In some embodiments, the determination model can be a machine learning model, such as a deep neural network (DNN) model.

[0167] In some embodiments, the input of the determination model may include device location information of the integrated signal analyzer, user information of the integrated signal analyzer, and candidate test parameters. The output of the determination model may be analysis difficulty.

[0168] In some embodiments, the determination model can be obtained by training based on a large number of first training samples with a first label. The remote terminal can input the plurality of first training samples with the first label into the initial determination model, construct a loss function based on the first label and the result of the initial determination model, and iteratively update the initial determination model based on the loss function. Model training is completed when preset conditions are met, resulting in a trained determination model. The preset conditions may include convergence of the loss function, reaching a threshold number of iterations, etc.

[0169] In some embodiments, the first training sample for training the determination model may be sample device location information, sample user information, and sample candidate test parameters of a sample integrated signal analyzer in the historical data. The first label may be the actual analysis difficulty corresponding to the first training sample in the historical data, which may be the average of the user test scores corresponding to the sample integrated signal analyzer.

[0170] In some embodiments, as Figure 4 As shown, the input of the determination model 420 may also include the grouping information 330 of the integrated signal analyzer.

[0171] Correspondingly, when the input of the determination model includes grouping information, the first training sample may also include the sample device location information of the aforementioned sample integrated signal analyzer, sample user information, and sample grouping information corresponding to the sample candidate test parameters.

[0172] For more information about grouping, see Figure 3 and its related descriptions.

[0173] In some embodiments of this specification, by considering grouping information, it is possible to better adapt to different signal environments and test scenarios, thereby improving the adaptability and accuracy of the determination model.

[0174] In some embodiments of this specification, based on the device location information and user information of the integrated signal analyzer, the analysis difficulty can be determined more accurately by determining the model, thereby improving the universal applicability of subsequent tests.

[0175] Figure 5 This is an exemplary flow chart for determining the first fault information and the second fault information according to some embodiments of this specification. Figure 5 As shown, the process 500 includes the following steps: In some embodiments, the process 500 can be executed by a remote terminal.

[0176] In some embodiments, the remote terminal can determine the abnormal value of the integrated signal analyzer based on the user's user test score; determine the first fault information through a judgment model based on the abnormal value and the latest maintenance result of the integrated signal analyzer; in response to determining that the integrated signal analyzer has a fault based on the first fault information, generate a maintenance instruction and send it to the management terminal; in response to obtaining the maintenance result from the management terminal, determine the second fault information of the integrated signal analyzer based on the maintenance result.

[0177] For information about integrated signal analyzers, remote terminals, and management terminals, see Figure 1 and its related descriptions.

[0178] Step 510 : determining an outlier of the integrated signal analyzer based on the user test score of the user.

[0179] An outlier is a value used to measure the likelihood of an anomaly in a comprehensive signal analyzer. For example, an outlier can be represented by a numerical value. A larger outlier value indicates a higher likelihood of an anomaly in the comprehensive signal analyzer.

[0180] In some embodiments, the remote terminal can determine the outlier value of the integrated signal analyzer based on the user's user test score in various ways. For example, the remote terminal can calculate the average of the user test scores corresponding to all tests performed by the user before the current test, as well as the average of the user test scores corresponding to all tests including the current test; and then use the absolute value of the difference between the two averages as the outlier value of the integrated signal analyzer corresponding to the user.

[0181] Step 520 : determining first fault information through a judgment model based on the abnormal value and the latest inspection result of the integrated signal analyzer.

[0182] The inspection result refers to the actual inspection result of the faulty integrated signal analyzer and its fault type. For example, the inspection result may be that integrated signal analyzer A is faulty and the fault type is component damage.

[0183] The faulty integrated signal analyzer obtained during actual maintenance refers to an integrated signal analyzer that is found to have abnormal functions or performance degradation during maintenance, inspection or repair.

[0184] In some embodiments, the remote terminal may restart the test on the integrated signal analyzer in response to the troubleshooting result meeting a preset condition.

[0185] Restart testing refers to the operation of retesting the user based on a reselected integrated signal analyzer or an integrated signal analyzer that has been repaired.

[0186] The preset conditions are used to determine whether the number of integrated signal analyzers undergoing maintenance is excessive or the problem with an integrated signal analyzer is too severe. Excessively severe means that the severity level of the problem with the integrated signal analyzer is greater than the problem threshold.

[0187] The problem threshold refers to a threshold used to determine whether a problem with the integrated signal analyzer is too serious. In some embodiments, the problem threshold can be set by professional technicians or by system default.

[0188] The severity level is a scale used to quantify the severity of a problem with the integrated signal analyzer. For example, the severity level can be expressed as a numerical value, where a higher numerical value indicates a more severe problem with the integrated signal analyzer.

[0189] In some embodiments, the remote terminal may determine the severity level of the problem with the integrated signal analyzer by querying a third preset relationship table. The third preset relationship table may include a correspondence between the problems with the integrated signal analyzer and the severity levels. In some embodiments, the third preset relationship table may be determined based on the problems with the integrated signal analyzer in historical data and the actual severity levels.

[0190] In some embodiments of this specification, when the test cannot accurately reflect the actual level of the user due to a malfunction of the integrated signal analyzer, the effectiveness and accuracy of the test can be effectively ensured by restarting the test after repairing the integrated signal analyzer.

[0191] In some embodiments, the management terminal can push the maintenance instructions to the administrator to obtain the maintenance results of the integrated signal analyzer. Figure 5 Step 530 and its related description.

[0192] In some embodiments, the simulation test results may also include fault information, which may include first fault information and second fault information. The first fault information includes whether a fault has occurred. The content of the second fault information can be found in Figure 5 Step 540 and its related description.

[0193] The first fault information is information used to indicate whether the integrated signal analyzer has a fault. For example, if the first fault information is 0, it means that the integrated signal analyzer has not a fault; if the first fault information is 1, it means that the integrated signal analyzer has a fault.

[0194] In some embodiments, the remote terminal may determine the first fault information through a determination model based on abnormal values ​​and the latest maintenance results of the integrated signal analyzer.

[0195] The determination model refers to a model used to determine the first fault information. In some embodiments, the determination model can be a machine learning model, such as a deep neural network (DNN) model.

[0196] In some embodiments, the input of the decision model may include abnormal values ​​of the integrated signal analyzer and the latest maintenance result of the integrated signal analyzer. The output of the decision model may be the first fault information of the integrated signal analyzer.

[0197] In some embodiments, the judgment model can be obtained based on a large number of second training samples with second labels. The second training samples for training the judgment model can be sample abnormal values ​​and sample maintenance results of the sample integrated signal analyzer in the historical data. Among them, the sample maintenance result can be the nearest maintenance result when the sample abnormal value is obtained, etc., which is not limited here. The second label can be the actual first fault information corresponding to the second training sample in the historical data, and the actual first fault information can be the fault information actually detected by the sample integrated signal analyzer within a period of time after the sample abnormal value is obtained. For example, the actual first fault information can be the presence / absence of a fault detected within one day after the sample abnormal value is obtained.

[0198] In some embodiments, the training method of the judgment model is similar to the training process of the determination model, which can be seen in Figure 4 The related descriptions will not be repeated here.

[0199] In some embodiments, the remote terminal may determine a user test score of the user based on a user analysis result of the integrated signal analyzer; and determine the first fault information based on the user test score of the user.

[0200] In some embodiments, the remote terminal may determine the first fault information in a variety of ways based on the user test score of the user. For example, the remote terminal may determine the first fault information by the following steps:

[0201] S1. Calculate the average of the user test scores corresponding to all users using the integrated signal analyzer.

[0202] S2. Calculate the average of the historical test scores corresponding to all users of the aforementioned integrated signal analyzer.

[0203] S3. Subtract the data obtained from S1 and S2 above and take the absolute value.

[0204] S4. Divide the absolute value obtained in S3 by the data obtained in S2.

[0205] S5. If the data obtained in response to S4 is greater than the test error, the integrated signal analyzer has a fault, that is, the first fault information is 1; otherwise, the first fault information is 0.

[0206] For example, if the data obtained in response to S4 is greater than the test error, it indicates that there may be a large deviation in the test, which has exceeded the range corresponding to the normal test, indicating that the integrated signal analyzer has a fault.

[0207] The test error refers to a threshold value used to determine whether the integrated signal analyzer has a fault. In some embodiments, the test error can be set by a professional technician or by system default.

[0208] In some embodiments of this specification, the effectiveness of the test may be affected by the status of the integrated signal analyzer. By accurately determining the status of the integrated signal analyzer reflected by the test, it is possible to ensure that the test results can truly reflect the actual level of the user, thereby improving the effectiveness of the test.

[0209] Step 530 : In response to determining that the integrated signal analyzer has a fault based on the first fault information, a maintenance instruction is generated and sent to the management terminal.

[0210] A maintenance instruction is an instruction pushed to an administrator to perform maintenance operations. For example, the maintenance instruction can be a machine instruction such as binary code.

[0211] In some embodiments, the remote terminal may generate a maintenance instruction and send it to the management terminal in response to determining that the integrated signal analyzer has a fault based on the first fault information (for example, in response to the first fault information being 1).

[0212] Step 540 : In response to obtaining the maintenance result from the management terminal, determine second fault information of the integrated signal analyzer based on the maintenance result.

[0213] The second fault information refers to the information used to characterize the faulty integrated signal analyzer and its fault type. For example, the second fault information can be represented by {(a1, b1), (a2, b2) ... (a i , b i )……,(a n , b n )}. Among them, a iThe malfunction indicating comprehensive signal analyzer can be determined based on a device number of the comprehensive signal analyzer, etc. i The comprehensive signal analyzer a i The corresponding fault type.

[0214] The fault type refers to the type of malfunction of the comprehensive signal analyzer. For example, the fault type can be represented by a numerical value or a letter. For example only, in response to the fault type being 1 or A, it can be represented that the fault type of the comprehensive signal analyzer belongs to component damage, etc., which is not limited herein.

[0215] In some embodiments, the remote terminal can obtain the maintenance result of the comprehensive signal analyzer from the management terminal in response to the maintenance result, and take the maintenance result as the second fault information of the comprehensive signal analyzer.

[0216] In some embodiments of the present specification, the abnormal value of the comprehensive signal analyzer is determined based on the test score of the user, and the first fault information is determined in combination with the latest maintenance result and the determination model, which helps to improve the accuracy of determining the first fault information. In addition, the remote terminal can automatically generate and push the maintenance instruction to the management terminal in response to determining that the comprehensive signal analyzer has a fault based on the first fault information, and further perform troubleshooting, so as to obtain the maintenance result. And determine the second fault information of the comprehensive signal analyzer based on the maintenance result, which helps to further improve the accuracy of the fault diagnosis of the comprehensive signal analyzer, and ensures the stable operation and reliability of the test.

[0217] It should be noted that the above description of the process 500 is only for example and illustration, and does not limit the scope of the present specification. Those skilled in the art can make various modifications and changes to the process 500 under the guidance of the present specification. However, these modifications and changes are still within the scope of the present specification.

[0218] The above has described the basic concept, and it is obvious that the above detailed disclosure is only for example and does not constitute a limitation on the present specification. Although it is not explicitly stated here, those skilled in the art can make various modifications, improvements and modifications to the present specification. Such modifications, improvements and modifications are suggested in the present specification, so such modifications, improvements and modifications still belong to the spirit and scope of the exemplary embodiments of the present specification.

[0219] Also, the use of "a" or "an" or "the" or "at least one" or "one or more" or "one or more instances" throughout the specification try to convey a similar meaning as the term "one or more" unless the context clearly dictates otherwise. The terms "comprising," "including," "containing," and "having" are intended to be open-ended terms. Likewise, the term "comprises" is synonymous with "includes" or "contains" for purposes of the specification and claims. Therefore, use of these terms is not intended to limit the scope of the disclosure to the specific embodiments discussed. Furthermore, the terms "first," "second," "third," and the like are used merely to distinguish one element from another, and do not require that the elements be in any particular order. It is also noted that various implementations of the disclosure have been described as comprising, including, containing, comprising, having or any other comparable term. However, the term "comprising" is used herein to mean the open-ended term "including but not limited to," and thus should be interpreted to cover the terms "consisting of" and "consisting essentially of" and their grammatical equivalents. In other words, the phrase "comprising" should be interpreted as including the more restrictive phrases "consisting of" and "consisting essentially of."

[0220] Furthermore, the order of presentation of the processes and methods of aspects of the present disclosure is not limited to the order in which those processes and methods are recited in the specification unless a strict order is otherwise specified. Although the above disclosure discusses some presently preferred embodiments of the application, it is to be understood that the application is not limited to the details of the foregoing, which are illustrative only. Additional embodiments of the application will readily occur to those skilled in the art. For example, although the system components described above can be implemented by hardware devices, they can also be implemented by software solutions, such as installing the described system on an existing server or mobile device.

[0221] Similarly, it is to be noticed that the term "comprising", used in the description, is not used in the sense of "consisting only of" to limit the present application to the specific embodiments. Limiting other embodiments with the terms "consisting only of" or "consisting of" or "which" is of course to be avoided.

[0222] Some embodiments use numerical values to describe components, quantities of attributes. It is to be understood that such numerical values used in the description of the embodiments are in some examples modified by the adjectives "about", "approximately", or "generally". Unless otherwise stated, "about", "approximately", or "generally" indicates that the number can vary by ±20%. Accordingly, numerical parameters such as those included in the application and claims are approximations. Although the numerical parameters are approximations, the numerical values set forth in the specific examples are reported as precisely as practicable. The numerical values of some embodiments consist of the numerical values desired. In some embodiments, numerical values are determined without considering significant digits before the decimal point and are rounded, according to the normal rules of rounding.

[0223] Each patent, patent application, patent application publication, and other materials, such as articles, books, specifications, publications, and documents, cited in this specification is hereby incorporated by reference in its entirety. This includes application history documents that are inconsistent with or conflict with the content of this specification, as well as documents (currently or subsequently attached to this specification) that limit the broadest scope of the claims of this specification. It should be noted that if the descriptions, definitions, and / or terminology used in the accompanying materials are inconsistent or conflicting with the content of this specification, the descriptions, definitions, and / or terminology used in this specification will control.

[0224] Finally, it should be understood that the embodiments described in this specification are intended only to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, by way of example and not limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly described and illustrated in this specification.

Claims

1. A comprehensive signal evaluation system, characterized in that: The system includes at least one integrated signal analyzer and a remote terminal; the integrated signal analyzer includes a communication module, a signal generation module, a spectrum analysis module, an index test module, a map location module, and an analysis and training module; The communication module is configured to perform data transmission with the signal generation module, the spectrum analysis module, the index testing module, the map location module, and the analysis and training module; The signal generation module includes a parameter submodule and a transmission submodule; The signal generating module is configured to: generate and transmit a first signal and / or generate and transmit a second signal through the transmitting submodule based on transmission parameters; the transmission parameters include a transmission order of the plurality of first signals, a transmission order of the plurality of second signals, a frequency, a duration, and a number of transmissions; The parameter submodule is configured to generate and transmit the first signal, wherein the first signal includes a frequency modulation signal, an amplitude modulation signal, a pulse signal, a swept frequency signal, and at least one type of first digital modulation signal; the transmission submodule is configured to generate and transmit the second signal, wherein the second signal includes at least one of an analog modulation signal, a second digital modulation signal, a digital intercom signal, a digital transmission cheating signal, a cellular communication signal, and a radar signal; The spectrum analysis module is configured to: obtain a user analysis operation, execute the user analysis operation and return a user analysis result; the user analysis operation includes at least one of frequency sweep, channel power measurement, occupied bandwidth measurement, time domain measurement, analog demodulation, voice demodulation, digital demodulation, IQ data acquisition and playback; The indicator test module is configured to: obtain a user test operation, execute the user test operation and return a test result; the user test operation includes a semi-automatic test of a test item; the test item is at least one of monitoring sensitivity, level measurement error, frequency stability monitoring, scanning speed monitoring and receiver spurious; The map location module is configured to: provide device location information and user information of the integrated signal analyzer; the user information includes the clock-in person and / or clock-in time of the integrated signal analyzer; The analysis and training module includes a learning submodule and a training submodule; The learning submodule is configured to: push learning content to users based on the learning content library; The training submodule is configured to: obtain training signal data based on user configuration parameters, and generate test questions based on the training signal data; in response to obtaining the user analysis result, upload the user analysis result to the remote terminal; The remote terminal is configured as follows: Acquire the device location information and the user information of the integrated signal analyzer through the map location module; Determining simulation test parameters based on the device location information and the user information, and sending the simulation test parameters to the integrated signal analyzer; the simulation test parameters include transmission parameters of the integrated signal analyzer; In response to obtaining the user analysis result of the integrated signal analyzer, a simulation test result is determined based on the user analysis result; the simulation test result includes a user test score of the user.

2. The system according to claim 1, wherein: The remote terminal is further configured to: Determining grouping information of the integrated signal analyzer based on the device location information and the user information of the integrated signal analyzer, where the grouping information includes at least one of a transmitting group, a receiving group, and an interference group; The simulation test parameters are determined based on the grouping information of the integrated signal analyzer.

3. The system according to claim 2, characterized in that The remote terminal is further configured to: Identify candidate test parameters; determining an analysis difficulty based on the candidate test parameters; The simulation test parameters are determined based on the analysis difficulty.

4. The system according to claim 1, wherein: The simulation test result further includes fault information, the fault information includes first fault information, and the first fault includes whether a fault occurs; the remote terminal is further configured to: Determining the user test score of the user based on the user analysis result of the comprehensive signal analyzer; The first fault information is determined based on the user test score of the user.

5. The system according to claim 4, characterized in that The fault information further includes second fault information, wherein the second fault information includes the integrated signal analyzer that has failed and the fault type; the system further includes a management terminal; the management terminal is configured to push a maintenance instruction to an administrator and obtain a maintenance result; the remote terminal is further configured to: determining an outlier value of the integrated signal analyzer based on the user test score of the user; Determining the first fault information through a judgment model based on the abnormal value and the latest maintenance result of the integrated signal analyzer; In response to determining that the integrated signal analyzer has a fault based on the first fault information, generating the maintenance instruction and sending it to the management terminal; In response to acquiring the maintenance result from the management terminal, the second fault information of the integrated signal analyzer is determined based on the maintenance result.

6. A comprehensive signal evaluation method, characterized in that: Executed by the integrated signal evaluation system according to claim 1, the method comprises: Obtain device location information and user information of the integrated signal analyzer through the map location module; Determining simulation test parameters based on the device location information and the user information, and sending the simulation test parameters to the integrated signal analyzer; the simulation test parameters include transmission parameters of the integrated signal analyzer; In response to obtaining the user analysis result of the integrated signal analyzer, a simulation test result is determined based on the user analysis result; the simulation test result includes a user test score of the user.

7. The method according to claim 6, characterized in that The method comprises: Determining grouping information of the integrated signal analyzer based on the device location information and the user information of the integrated signal analyzer, where the grouping information includes at least one of a transmitting group, a receiving group, and an interference group; The simulation test parameters are determined based on the grouping information of the integrated signal analyzer.

8. The method according to claim 6, characterized in that The simulation test result further includes fault information, the fault information includes first fault information, and the first fault includes whether a fault occurs; the method further includes: Determining the user test score of the user based on the user analysis result of the comprehensive signal analyzer; The first fault information is determined based on the user test score of the user.

9. A comprehensive signal evaluation device, characterized in that The apparatus comprises at least one processor and at least one memory; The at least one memory is for storing computer instructions; The at least one processor is configured to execute at least part of the computer instructions to implement the integrated signal evaluation method according to any one of claims 6 to 8.

10. A computer-readable storage medium storing computer instructions, wherein when a computer reads the computer instructions in the storage medium, the computer executes the integrated signal evaluation method according to any one of claims 6 to 8.

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