Comprehensive signal evaluation system and method

Abstract

The embodiment of the invention discloses a comprehensive signal evaluation system and method. The system comprises at least one comprehensive signal analyzer and a remote terminal, the comprehensive signal analyzer comprises a communication module, a signal generation module, a spectrum analysis module, an index test module, a map position module and an analysis training module; the remote terminal is configured to obtain equipment position information and user information of the comprehensive signal analyzer through the map position module; based on the equipment position information and the user information, simulation test parameters are determined, and the simulation test parameters are sent to a comprehensive signal analyzer; in response to the obtained user analysis result of the comprehensive signal analyzer, determining a simulation test result based on the user analysis result; the simulation test result comprises a user test score of the user.

Description

Technical Field

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

[0002] In the current field of signal analysis, integrated signal analyzers have become key tools for tasks such as radio signal identification, search, 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 the signal. When users encounter unknown waveforms, they usually need to perform a series of analyses, including obtaining key information such as the signal's spectrum, energy spectrum, and power spectrum. To this end, users need to adjust multiple parameters, such as scan time, frequency scan range, resolution bandwidth, attenuator attenuation amplitude, and center frequency, to ensure the accuracy and effectiveness of the analysis. However, in the case of multi-machine joint testing, it is impossible to accurately set the signal sending parameters of multiple signal analyzers during linkage simulation analysis, and the processing method of the simulation test results is unclear, making it difficult to accurately evaluate the performance of the signal analyzer and the effect 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 linkage simulation analysis; and to improve the evaluation accuracy of the simulation analysis effect of the comprehensive signal analyzers. Summary of the invention

[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 perform data transmission 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 a transmission order of multiple first signals, a transmission order of multiple second signals, a frequency point, a duration and a 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 tests 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 device location information and user information of the integrated signal analyzer; the user information includes the punch-in personnel and / or punch-in time of the integrated signal analyzer; the analysis and training module includes learning sub module and 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 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, a simulation test result is determined based on the user analysis result; the simulation test result includes a user test score of the user. ;

[0005] One of the embodiments of the present specification provides a comprehensive signal evaluation method, the method comprising: 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 the present 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; 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 of the embodiments of the present 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 by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:

[0009] Figure 1 is an exemplary module diagram of a comprehensive signal evaluation system according to some embodiments of the present 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 this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, this specification can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0015] It should be understood that the "system", "device", "unit" and / or "module" used herein are a method for distinguishing different components, elements, parts, portions 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 this specification and claims, unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "comprise" and "include" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0017] Flowcharts are used in this specification to illustrate the operations performed by the system according to the embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed precisely in order. Instead, the steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or one or more operations may be removed from these processes.

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

[0019] In some embodiments, Figure 1 As shown, the integrated signal evaluation system 100 may include at least one integrated signal analyzer 110, a remote terminal 120 and a management terminal 130. The integrated signal analyzer 110 may 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 and training module 116. The signal generation module 112 includes a parameter submodule 112-1 and a transmission submodule 112-2, and the analysis and training module 116 includes a learning submodule 116-1 and a training submodule 116-2.

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

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

[0022] The communication module 111 refers to 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 may 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 refers to a module that can generate and transmit a signal in a custom manner. 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] Digital modulation signals refer to signals that convert digital data into signals suitable for transmission over a communication channel. For example, digital modulation signals may include, but are not limited to, binary phase shift keying (BPSK) signals, differentially coherent binary phase shift keying (DBPSK) signals, quadrature phase shift keying (QPSK) signals, 8Phase ShiftKeying (8PSK) signals, etc.

[0028] In some embodiments, the digital modulation signal may include a first digital modulation signal and a second digital modulation signal, wherein the first digital modulation signal refers to a digital modulation signal generated and transmitted by a parameter submodule.

[0029] The transmitting submodule 112-2 refers to a module that can support single or cyclic transmission of multiple signals in a user-defined sequence, frequency, and duration. In some embodiments, the transmitting submodule 112-2 may include a rich signal wave file library.

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

[0031] The second signal refers to a service signal generated and transmitted by the transmitting submodule. In some embodiments, the second signal may include but is not limited to an analog modulation signal, a second digital modulation signal, a digital intercom signal, a digital transmission cheating signal, a cellular communication signal, a radar signal, and other common service signals. Among them, the service signal refers to a signal used to transmit service data.

[0032] The second digital modulation signal is similar to the first digital modulation signal, except that the second digital modulation signal is generated and transmitted by the transmitting submodule.

[0033] In some embodiments, the signal generating module 112 is used to generate and transmit a first signal and / or a second signal through a transmitting submodule 112-2 based on the transmission parameters. For example, the signal generating module 112 can generate and transmit a first signal and / or a second signal through a transmitting submodule 112-1 based on the reference table and according to the frequency in the transmission parameters. As an 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 transmitting submodule, etc., without limitation here.

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

[0035] Transmission parameters refer to parameters related to signal transmission. For example, the transmission parameters may include but are not limited to the transmission order of multiple first signals, the transmission order of multiple second signals, the 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 communication 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 the 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 operations involved when a user inputs instructions or parameters through the interface of the integrated signal analyzer to perform specific analysis tasks. In some embodiments, user analysis operations may include but are not limited to frequency sweeping, measuring channel power, measuring occupied bandwidth, time domain measurement, analog demodulation, voice demodulation, digital demodulation, IQ data acquisition and playback, etc. Among them, frequency sweeping may include but are not limited to background signal acquisition, automatic signal discovery, peak signal search, one-click software screenshot, Marker difference calculation and other shortcut functions.

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

[0042] The indicator testing module 114 refers to 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 the viewing of test history records, the resumption of testing from breakpoints, and the generation of a test report with one click after the test is completed.

[0044] User test operations refer to operations involved in executing specific test tasks through commands or parameters input 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 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.

[0046] The test result refers to the result returned after the user performs the user test operation. For example, the test result can be expressed as a numerical value, and 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 description.

[0049] In some embodiments, the signal source can be used as an interference source in the interference search project of the radio technology drill 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 information of the clocking-in user can be reported to the remote terminal through the clocking-in function. The remote terminal can receive real-time information such as the clocking-in personnel, clocking-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 refers to 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, and individual signals also provide a demonstration video of signal analysis.

[0052] The training submodule 116-2 is a module for providing test questions to the user to test the user. In some embodiments, 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, the user analysis result is uploaded to the remote terminal 120.

[0053] In some embodiments, the training guidance step of the training submodule 116-2 can guide the user to complete a complete process of signal generation and analysis, obtain the user analysis result, and finally provide the user analysis result to the remote terminal. Among them, the step provides a detailed operation method and provides user configuration parameters.

[0054] User configuration parameters refer to the parameters related to the signal received by the integrated signal analyzer adjusted by the user. For example, user configuration 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, the user configuration parameters may be set by a professional technician or by system default.

[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 test 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 use it as a test question.

[0060] The remote terminal 120 refers to a hardware device used to interact with the integrated signal analyzer 110 and perform operations. For example, the remote terminal may include one or any combination of devices with input and / or output functions such as a mobile device, a tablet computer, a laptop computer, a desktop computer, etc. In some embodiments, the remote terminal 120 may also include an input device, an output device, etc. The input device may include a keyboard, a touch screen, a voice device, etc., or any combination thereof. The output device may include a display, a speaker, a printer, etc., 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 obtaining the user analysis results of the integrated signal analyzer, determine the simulation test results based on the user analysis results. For the content of this embodiment, please refer to Figure 2 and its related description.

[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 description.

[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. For details about this embodiment, please refer to Figure 3 and its related description.

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

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

[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 description.

[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 comprehensive signal analyzer; and determine the first fault information based on the user test score of the user. For details about this embodiment, please refer to Figure 5 and its related description.

[0068] In some embodiments, the remote terminal 120 is further configured to determine the abnormal value of the integrated signal analyzer based on the user test score of the user; determine the first fault information through the 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. For the content of this embodiment, please refer to Figure 5 and its related description.

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

[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 program, 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 description.

[0072] It should be noted that the above description of the system and platform is only for convenience of description and does not limit the present specification to the scope of the embodiments. It is understandable that, after understanding the principle of the system, those skilled in the art may arbitrarily combine the modules or form a subsystem to connect with other modules without deviating from the principle.

[0073] Figure 2 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 obtaining the user analysis results of 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 description.

[0076] Step 210, obtaining 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 can 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] User information refers to the information of the user who uses the integrated signal analyzer. For example, the user information may include but is not limited to the person who punches in and out of the integrated signal analyzer, the punching in time, etc.

[0080] In some embodiments, the remote terminal can obtain the user who uses the integrated signal analyzer and the user's clock-in time through an application in the map location module (eg, an application for user login and clock-in, etc.).

[0081] Step 220, based on the device location information and user information, determine the simulation test parameters, and send the simulation test parameters to the integrated signal analyzer.

[0082] The simulation test parameters refer to the parameters used to configure and adjust the signal transmitting device (for example, a comprehensive signal analyzer used to transmit signals) when performing a signal simulation test. For example, the simulation test parameters may include but are not limited to the transmission parameters of at least one comprehensive signal analyzer.

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

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

[0085] In some embodiments, the question bank may be pre-set by professional technicians or the system.

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

[0087] The vector database refers to a database used to determine test questions. In some embodiments, the vector database includes a plurality of reference vectors and a reference test question corresponding to each reference vector.

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

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

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

[0091] For other embodiments of determining simulation test parameters based on device location information and user information of a comprehensive signal analyzer, see Figure 3 and its related description.

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

[0093] The user analysis result refers to the data on the signal-related parameters analyzed by the user. For example, the user analysis result may include but is 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 test score of the user.

[0097] The user test score is an indicator used to quantify the user's performance in the test. For example, the higher the user test score, the better the user's performance in the test, that is, the better the simulation test result.

[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 also determine the user test score based on the analysis difficulty and the evaluation difficulty through a first preset rule. For example, the first preset rule may be that the higher the mean of the analysis difficulty and 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 description.

[0102] In some embodiments, the harder the test question is, the harder it is to score. In order to enable longitudinal comparison of the user's test scores, that is, to enable comparison between different tests (e.g., this test and the last test), it is important to consider the difficulty of the test question.

[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 vertically, 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 result of the integrated signal analyzer with all the transmission parameters of the integrated signal analyzer to obtain the user test score of the user. For example, the remote terminal may determine the simulation test score based on the user analysis result of the integrated signal analyzer by comparing the analyzed signal-related parameters (e.g., frequency, signal type) with the transmission parameters of the integrated signal analyzer.

[0105] For example, when comparing, for each signal parameter that needs to be analyzed (hereinafter referred to as sub-topic), if the user's analysis result is consistent with the transmission parameter, it is judged to be correct, otherwise it is wrong. Finally, the user's user test score is calculated by dividing the number of correct sub-topics by the number of all sub-topics, and the user's test accuracy is expressed as a percentage. For example, among 10 sub-topics, if the user has 4 correct answers in the frequency comparison and 3 correct answers in the signal type comparison, the user's user test score is 70%.

[0106] In some embodiments of the present specification, the integrated signal analyzer may include multiple functions, covering commonly used functions, and may also provide automated customized learning content to help users learn signal analysis. By providing users with different skill levels with test of analyzing signal simulation, the user's skill level may be further improved.

[0107] It should be noted that the above description of the process 200 is only for example and illustration, and does not limit the scope of application of this specification. For those skilled in the art, various modifications and changes can be made to the process 200 under the guidance of this specification. However, these modifications and changes are still within the scope of this specification.

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

[0111] Grouping information refers to a way of organizing information by dividing the participating integrated signal analyzers into different categories according to their functions during signal analysis or communication testing. For example, grouping information may include but is not limited to transmitting groups, receiving 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 signal and the receiving signal can be the same integrated signal analyzer. In some embodiments, in order to avoid interference from the transmitting party when the receiving party receives the signal, the transmitting signal and the receiving signal can also use different integrated signal analyzers. The specific situation is set by professional and technical personnel and is not limited here.

[0114] The interference group also includes at least one integrated signal analyzer specifically used to transmit interference signals. In some embodiments, similar to the receiving group, in order to prevent the receiving party from being interfered by the transmitted interference signal when receiving the signal, the integrated signal analyzers for transmitting the interference signal and the receiving signal can be different, but in some cases they can also be the same integrated signal analyzer. The specific situation is set by professional and technical personnel and is not limited here.

[0115] In some embodiments, the remote terminal may use the integrated signal analyzer logged in by the user as the receiving group in the grouping information; select a preset number of integrated signal analyzers from multiple integrated signal analyzers that the user has not logged in to as the transmitting group according to a second preset rule; and then use the remaining integrated signal analyzers as the interference group.

[0116] The second preset rule refers to a set of pre-set selection criteria or principles formulated in order to form a transmission group in signal analysis or communication testing. These rules are used to guide how to select a preset number of integrated signal analyzers from multiple integrated signal analyzers that are not logged in by users to form a transmission group. In some embodiments, the specific content of the second preset rule can be preset by professional technicians or the system according to test requirements and other conditions. For example, the second preset rule can be to select non-adjacent integrated signal analyzers as the transmission group, and non-adjacent can be non-adjacent in the physical location of the integrated signal analyzers, or non-adjacent in signal frequency allocation, etc., which is not limited here.

[0117] The preset number refers to determining the number of integrated signal analyzers in the transmission group based on the second preset rule.

[0118] In some embodiments, the preset number may be set by a professional technician or by system default.

[0119] In some embodiments, the grouping information may also include neighbor information between integrated signal analyzers. Figure 3 FIG. 1 is an exemplary schematic diagram of determining simulation test parameters according to some embodiments of this specification. Figure 3 As shown, the remote terminal may determine the evaluation difficulty 350 based on the device location information 310 and the user information 320 of the integrated signal analyzer; and determine the grouping information 330 of the integrated signal analyzer based on the evaluation difficulty 350 .

[0120] For more information about device location information and user information, see Figure 2 and its related description.

[0121] The adjacent information refers to the information of integrated signal analyzers that are physically adjacent in each group of group information (eg, transmission group, reception group, and interference group). For example, in the transmission group, integrated signal analyzer 1 and integrated signal analyzer 3 are physically adjacent.

[0122] Assessment difficulty refers to the process of assessing the ability level of the users participating in the test, and then matching and determining the test difficulty they can accept. For example, the assessment difficulty can be expressed as a numerical value, and an increase in the numerical value represents an increase in the assessment difficulty. Assessment difficulty is usually graded in a step-by-step manner, with each level corresponding to a different level of difficulty. As an example only, the assessment difficulty is divided into several levels, each with a clear numerical representation. For example, if there are 3 levels, then 1 may represent an easy difficulty, 2 represents a medium difficulty, and 3 represents a difficult 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 experience they have, the higher the evaluation difficulty for that user.

[0124] In some embodiments, the remote terminal can determine the evaluation difficulty in a variety of ways based on the device location information and user information. For example, the remote terminal can query the historical data for the user test score corresponding to each integrated signal analyzer that the user has logged into, and determine the average of the user test scores of all the aforementioned multiple integrated signal analyzers that have logged in as the evaluation difficulty of the user by querying the second preset relationship table.

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

[0126] In some embodiments, the remote terminal can determine the grouping information based on the above, and respond that the higher the difficulty of evaluation, the more integrated signal analyzers there are in the interference group, and the more integrated signal analyzers with physically adjacent locations there are in the transmission group.

[0127] In some embodiments of the present specification, 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 that are physically adjacent), the difficulty of the test questions can be effectively increased. This is because the more integrated signal analyzers there are in the interference group, the more complicated the steps of separating and analyzing the received signals will become, requiring a higher level of technology and more processing time; at the same time, the more clustered the integrated signal analyzers in the transmission group are, the easier it is for the transmitted signals to have a superposition effect, thereby increasing 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 the content of simulation test parameters, please refer to Figure 2 and its related descriptions.

[0131] In some embodiments, the remote terminal can sort the usage frequencies of simulation test parameters from high to low in the records of historical simulation tests, and select multiple simulation test parameters with higher rankings according to a preset quantity as candidate test parameters.

[0132] The preset quantity can be set in advance by professional technicians or the system. In some embodiments, the preset quantity can be adjusted according to the computing resources of the processor in the remote terminal, but it cannot be increased without limit under the response time limit. For example, if it is required to complete the response within 0.1 seconds, and under the current computing resources, the amount of computation that can be processed within 0.1 seconds is between a and b, and the amount of computation for calculating a candidate test parameter is x, then the value of the preset quantity should satisfy the condition of a < N * x < b to ensure the calculation and screening of candidate test parameters are completed within the specified response time. Here, N is the value of the preset quantity.

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

[0134] The historical test score refers to the user's test score in the historical data. For the content of the user test score, please refer to Figure 2 and its related descriptions.

[0135] The historical test parameter refers to the corresponding simulation test parameter in the historical data. For the content of the simulation test parameter, please refer to Figure 1 , Figure 2 and its related descriptions.

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

[0137] The most recent historical preset time period refers to a period of historical time close to the current moment. For example, the most recent 1 week, the most recent 1 month, etc., which are not limited here and can be set by professional technicians or the system by default.

[0138] Fluctuation data refers to the standard deviation of historical test scores divided 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 also determine the frequency threshold value through a third preset rule based on the number of candidate test parameters. As an example only, the third preset rule may be that the smaller the number of candidate test parameters, the higher the frequency threshold value.

[0143] In some embodiments, in response to the smaller number of candidate test parameters, the higher the frequency threshold is set, which can indicate that the user may be more inclined to use test questions that are more representative, more frequently used, and less likely to make mistakes. Those test questions that are less frequently used may be caused by the bias or unreasonableness of the test questions themselves. 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 test 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 also determine the fluctuation threshold value through a fourth preset rule based on the fluctuation data of the historical test scores of the users participating in the test. 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, in response to the greater the fluctuation data of the historical test scores of the users participating in the test, the fluctuation threshold should be set higher accordingly. This is because when the level differences of users are large, questions that can test the differences of users should be selected.

[0148] In some embodiments of the present 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] Analytical difficulty refers to the difficulty of analyzing the test questions based on the candidate test parameters. For example, analytical difficulty can be expressed as a numerical value, and the higher the numerical value, the greater the analytical difficulty.

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

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

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

[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 an 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 integrated signal analyzers that are physically adjacent 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 integrated signal analyzers that are physically adjacent 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 the present specification, grouping the integrated signal analyzers can determine the difficulty of the received test questions to a certain extent. If the difficulty of the test questions generated by the 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 also 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 closest to the evaluation difficulty as simulation test parameters.

[0159] The analysis difficulty that is 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, evaluation difficulty, and analysis difficulty, see Figure 3 Related description in the previous text.

[0161] In some embodiments of the present specification, the purpose of teaching students in accordance with their aptitude can be achieved 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.

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

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

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

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

[0166] The determination model refers to a model used to determine the difficulty of the analysis. In some embodiments, the determination model may 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 first labels. The remote terminal can input multiple first training samples with first labels into the initial determination model, construct a loss function through the first label and the result of the initial determination model, and iteratively update the initial determination model based on the loss function. When the preset conditions are met, the model training is completed and a trained determination model is obtained. Among them, the preset conditions can be that the loss function converges, the number of iterations reaches a threshold, etc.

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

[0170] In some embodiments, 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, the sample user information, and the corresponding sample grouping information under the sample candidate test parameters.

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

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

[0174] In some embodiments of the present 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 to subsequent tests.

[0175] Figure 5 is an exemplary flow chart for determining first fault information and 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 description.

[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 possibility of an abnormality in the integrated signal analyzer. For example, the outlier can be represented by a numerical value, and the larger the value of the outlier is, the more likely the integrated signal analyzer is to be abnormal.

[0180] In some embodiments, the remote terminal may determine the abnormal value of the integrated signal analyzer based on the user test score of the user in a variety of ways. For example, the remote terminal may calculate the average of the user test scores corresponding to all tests of the user before the current test, and 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 abnormal value of the integrated signal analyzer corresponding to the user.

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

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

[0183] The faulty integrated signal analyzer obtained through 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 satisfying 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 condition refers to a condition for judging that the number of integrated signal analyzers to be repaired is too large or the problem of the integrated signal analyzer is too serious. Among them, too serious means that the severity level corresponding to the problem of the integrated signal analyzer is greater than the problem threshold.

[0187] The problem threshold refers to a threshold used to determine whether the problem of 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 refers to a level used to quantify the severity of a problem of the integrated signal analyzer. For example, the severity level may be expressed as a numerical value, and a higher numerical value of the severity level indicates a more severe problem of the integrated signal analyzer.

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

[0190] In some embodiments of the present 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 instruction to the administrator, so as to obtain the maintenance result of the integrated signal analyzer. Figure 5 Step 530 and its related description.

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

[0193] The first fault information refers to information used to indicate whether the integrated signal analyzer has a fault. For example, when the first fault information is 0, it means that the integrated signal analyzer has no fault; when 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 may 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 determination model is similar to the training process of the determination model, which can be seen in Figure 4 And the related description will not be repeated here.

[0199] In some embodiments, the remote terminal may determine a 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.

[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 by 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. In response to the data obtained in S4 being 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, when the data obtained in response to S4 is greater than the test error, it indicates that the test may have a large deviation, which has exceeded the range corresponding to the normal test, which means that the integrated signal analyzer has a fault.

[0207] The test error refers to a threshold 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 state of the integrated signal analyzer. By accurately judging the state of the integrated signal analyzer reflected by the test, it can be ensured that the test result 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] The maintenance instruction refers to an instruction used to push to the administrator to perform maintenance operations. For example, the maintenance instruction may be a machine instruction such as a 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 the second fault information of the integrated signal analyzer based on the maintenance result.

[0213] The second fault information refers to 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 iIndicates the integrated signal analyzer that has failed, which can be determined based on the device number of the integrated signal analyzer, etc.; b i Indicates integrated signal analyzer a i The corresponding fault type.

[0214] The fault type refers to the specific type of fault of the integrated signal analyzer. For example, the fault type can be represented by a numerical value or a letter. As an example only, when the fault type is 1 or A, it can represent that the fault type of the integrated signal analyzer is a component damage, etc., which is not limited here.

[0215] In some embodiments, the remote terminal may obtain the maintenance result of the integrated signal analyzer from the management terminal in response and use the maintenance result as the second fault information of the integrated signal analyzer.

[0216] In some embodiments of this specification, the abnormal value of the integrated signal analyzer is determined based on the user's test score, and the first fault information is determined in combination with the latest maintenance results and the judgment model, which helps to improve the accuracy of determining the first fault information. In addition, when the remote terminal responds to determining that the integrated signal analyzer has a fault based on the first fault information, it can automatically generate and push maintenance instructions to the management terminal, and perform further troubleshooting to obtain the maintenance results. And based on the maintenance results, the second fault information of the integrated signal analyzer is determined, which helps to further improve the accuracy of the integrated signal analyzer fault diagnosis and ensure the stable operation and reliability of the test.

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

[0218] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only for example and does not constitute a limitation of this specification. Although not explicitly stated here, those skilled in the art may make various modifications, improvements and corrections to this specification. Such modifications, improvements and corrections are suggested in this specification, so such modifications, improvements and corrections still belong to the spirit and scope of the exemplary embodiments of this specification.

[0219] At the same time, this specification uses specific words to describe the embodiments of this specification. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of this specification. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different positions in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures or characteristics in one or more embodiments of this specification can be appropriately combined.

[0220] In addition, unless explicitly stated in the claims, the order of the processing elements and sequences described in this specification, the use of alphanumeric characters, or the use of other names are not intended to limit the order of the processes and methods of this specification. Although the above disclosure discusses some invention embodiments that are currently considered useful through various examples, it should be understood that such details are only for illustrative purposes, and the attached claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the essence and scope of the embodiments of this specification. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only by software solutions, such as installing the described system on an existing server or mobile device.

[0221] Similarly, it should be noted that in order to simplify the description disclosed in this specification and thus help understand one or more embodiments of the invention, in the above description of the embodiments of this specification, multiple features are sometimes combined into one embodiment, figure or description thereof. However, this disclosure method does not mean that the features required by the subject matter of this specification are more than the features mentioned in the claims. In fact, the features of the embodiments are less than all the features of the single embodiment disclosed above.

[0222] In some embodiments, numbers describing the number of components and attributes are used. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise specified, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may change according to the required features of individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining digits. Although the numerical domains and parameters used to confirm the breadth of their range in some embodiments of this specification are approximate values, in specific embodiments, the setting of such numerical values ​​is as accurate as possible within the feasible range.

[0223] Each patent, patent application, patent application publication, and other materials, such as articles, books, specifications, publications, documents, etc., cited in this specification are hereby incorporated by reference in their entirety. Except for application history documents that are inconsistent with or conflicting with the contents of this specification, documents that limit the broadest scope of the claims of this specification (currently or later attached to this specification) are also excluded. It should be noted that if the descriptions, definitions, and / or use of terms in the materials attached to this specification are inconsistent or conflicting with the contents described in this specification, the descriptions, definitions, and / or use of terms in this specification shall prevail.

[0224] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, as an example and not a 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 introduced and described in this specification.

Claims

1. A comprehensive signal evaluation system, characterized in that: 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 perform data transmission 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 generating module is configured to: based on the transmission parameters, generate and transmit the first signal through the parameter submodule and / or generate and transmit the second signal through the transmission submodule; the transmission parameters include the transmission order of the plurality of the first signals, the transmission order of the plurality of the 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 frequency sweep 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 a user analysis result; the user analysis operation includes at least one of frequency sweeping, measuring channel power, measuring occupied bandwidth, time domain measurement, analog demodulation, voice demodulation, digital demodulation, IQ data acquisition and playback; The index 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 the user based on the learning content library; The training submodule is configured to: acquire training signal data based on user configuration parameters, and generate test questions based on the training signal data; in response to acquiring 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; 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 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, characterized in that The remote terminal is further configured to: Determine grouping information of the integrated signal analyzer based on the device location information and the user information of the integrated signal analyzer, wherein 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: determining candidate test parameters; determining the 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, characterized in that The simulation test result also 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 as follows: 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 having a fault and its 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; Based on the abnormal value and the latest maintenance result of the comprehensive signal analyzer, determining the first fault information through a judgment model; 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 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 transmission parameters of the integrated signal analyzer; In response to obtaining the user analysis result of the comprehensive 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: Determine grouping information of the integrated signal analyzer based on the device location information and the user information of the integrated signal analyzer, wherein 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 also includes fault information, the fault information includes first fault information, and the first fault includes whether a fault occurs; the method also 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 used to store 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, wherein the storage medium stores computer instructions. 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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