Dual-mode communication unit frequency modulation method based on adaptive algorithm

Abstract

The invention discloses a dual-mode communication unit frequency modulation method based on an adaptive algorithm, relates to the technical field of communication, and aims to solve the problems that the traditional communication method is prone to signal instability in a special working environment, so that the communication is interrupted repeatedly, the working continuity and safety are influenced, the transmission efficiency is low, and the communication efficiency is low. The method comprises the following steps: acquiring and analyzing environment parameters, and acquiring special working environment parameters; the temperature (T), humidity (H) and electromagnetic interference intensity (E) parameters in a special working environment are acquired through various high-precision sensors, and the sensors are calibrated, so that the communication mode can be automatically adjusted according to the change of the special working environment by accurately acquiring the environmental parameters, comprehensively evaluating the communication quality and flexibly adjusting the communication frequency; the problems of unstable signal and low transmission efficiency of traditional communication in a special environment are solved.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and more specifically, to a frequency modulation method of a dual-mode communication unit based on an adaptive algorithm. Background Art

[0002] In today's era of rapid technological development, communication technology plays a vital role in all fields. However, in many special working environments, such as high temperature, high humidity, strong electromagnetic interference, etc., traditional communication methods often face severe challenges.

[0003] When the signal is unstable, it may cause repeated interruptions in communication, affecting the continuity and safety of work. Low transmission efficiency will waste time and resources and reduce work efficiency. In order to overcome these difficulties and improve the reliability and adaptability of communication, we propose a frequency modulation method for dual-mode communication units based on an adaptive algorithm. Summary of the invention

[0004] The purpose of the present invention is to provide a dual-mode communication unit frequency modulation method based on an adaptive algorithm to solve the technical problem that traditional communication methods are prone to signal instability in special working environments, resulting in repeated communication interruptions, affecting the continuity and safety of work, resulting in low transmission efficiency, wasting time and resources, and reducing work efficiency.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a frequency modulation method of a dual-mode communication unit based on an adaptive algorithm, comprising the following steps:

[0006] S1. Collect and analyze environmental parameters;

[0007] S101, collection of special working environment parameters;

[0008] The temperature (T), humidity (H), and electromagnetic interference intensity (E) parameters in special working environments are collected through a variety of high-precision sensors. The sensors are calibrated to accurately sense subtle changes in the environment, and the collected formulas are used to provide a basis for the frequency adjustment of the communication unit.

[0009] S102, in-depth analysis of environmental parameters;

[0010] Conduct an in-depth analysis of the collected environmental parameters and use the judgment formula to determine whether the current environment is suitable for Mode A communication. During the analysis, the communication unit will use advanced data analysis algorithms to compare the collected environmental parameters with the preset applicable range of Mode A. If the environmental parameters are within the applicable range of Mode A, Mode A will continue to be used for communication; if the environmental parameters are beyond the applicable range of Mode A, proceed to the next step.

[0011] S2. Evaluate communication quality;

[0012] S201, automatic mode switching;

[0013] When communication in mode A is affected, the communication unit automatically switches to mode B. The switching process is fast and smooth to ensure that communication will not be interrupted. During the switching, the communication unit will record the reason and time of the switching for subsequent analysis and optimization.

[0014] S202, comprehensive assessment of communication quality;

[0015] Comprehensively evaluate the communication quality of mode B. The evaluation indicators include signal strength (S), bit error rate (BER), and transmission rate (R). To ensure the accuracy of the evaluation, the communication unit will monitor the changes in signal strength in real time, count the frequency of bit error rate, and measure the transmission rate. By evaluating the above indicators based on the evaluation formula, we can understand the communication effect of mode B in the current environment and provide a reference for subsequent frequency adjustment.

[0016] S3, adjust the communication frequency;

[0017] S301, adaptive algorithm;

[0018] According to the evaluation results, the adaptive algorithm automatically adjusts the frequency (F) of the communication unit based on the adjustment formula. The adjustment methods are flexible and diverse. The frequency can be gradually adjusted within a certain range to find the best communication frequency, or it can quickly switch to a specific frequency according to the preset frequency adjustment strategy. During the frequency adjustment process, the communication unit will continuously monitor the communication quality and adjust the speed and direction of the frequency adjustment in real time according to the changes in the communication quality.

[0019] S302, frequency adjustment strategy;

[0020] In the process of adjusting the frequency, the communication unit will also take into account the changes in the surrounding environment and the influence of interference from other communication devices. If the above factors affect the communication quality, the communication unit will adjust the frequency adjustment strategy in time to ensure that the best frequency that can meet the communication needs is found;

[0021] S4, real-time monitoring;

[0022] S401, collation and analysis of monitoring data;

[0023] After adjusting the frequency, the communication unit continues to monitor the environmental parameters and communication quality in real time. The monitoring process is continuous and will not be interrupted by other operations of the communication unit. The communication unit will regularly organize and analyze the monitored data to timely detect changes in environmental parameters and communication quality;

[0024] S402, frequency adjustment optimization;

[0025] If the environmental parameters change or the communication quality decreases, the adaptive algorithm will start again and readjust the communication frequency. In the process of readjusting the frequency, the communication unit will draw on the previous adjustment experience to speed up the adjustment and improve the accuracy of the adjustment;

[0026] S5, intelligent learning model;

[0027] S501, communication data storage;

[0028] During operation, the communication unit continuously accumulates communication data in different environments. These data include environmental parameters, communication mode, frequency, and communication quality information. Data accumulation is a continuous process. The communication unit will record and store each communication data for subsequent analysis and learning.

[0029] S502, deep learning model;

[0030] Through the intelligent learning model, the data is deeply analyzed and learned based on the learning formula, and the mapping relationship between environmental parameters and optimal communication frequency is established. The intelligent learning module will use advanced machine learning algorithms to analyze and process a large amount of communication data and extract useful information and rules from it. With the continuous accumulation of data, the communication unit can more accurately predict the optimal communication frequency in a specific environment.

[0031] S503, predicting the optimal communication frequency range;

[0032] In practical applications, the intelligent learning module can predict the possible optimal communication frequency range based on historical data, thereby speeding up the frequency modulation speed. The intelligent learning module will predict the most likely optimal communication frequency range based on the current environmental parameters and historical data. When adjusting the frequency, the communication unit can search within this range first, thereby greatly speeding up the frequency modulation speed.

[0033] S6, dynamic power adjustment;

[0034] S601, adjusting the transmission power in real time according to environmental parameters and communication quality;

[0035] In addition to adjusting the communication frequency, the transmission power (P tx ), dynamic power adjustment is a real-time process. The communication unit will adjust the transmission power in real time according to the changes in environmental parameters and communication quality and based on the power adjustment formula;

[0036] S602, automatically adjusting the transmission power according to environmental interference;

[0037] Under the premise of ensuring communication quality, reducing the transmission power can reduce energy consumption and extend the working time of the communication unit. When the environmental interference is large, the transmission power can be appropriately increased to enhance the signal strength and improve the reliability of communication. The communication unit will automatically adjust the transmission power according to the degree of environmental interference and the requirements of communication quality to achieve the best communication effect;

[0038] S7, multi-sensor fusion;

[0039] Adopting multi-sensor fusion technology, different types of sensor data are integrated and analyzed. In addition to temperature, humidity and electromagnetic interference intensity sensors, air pressure sensors, vibration sensors and other types of sensors are also integrated. Through comprehensive analysis of multiple sensor data, environmental conditions can be judged more accurately, providing more abundant information for the adaptive algorithm. The communication unit will use advanced data analysis algorithms and fusion formulas to fuse and analyze multiple sensor data, extract useful information and rules from them, and provide more accurate and comprehensive environmental information for the adaptive algorithm.

[0040] S8, fault self-diagnosis and recovery;

[0041] The communication unit has a fault self-diagnosis function. When a communication fault occurs, it can automatically detect the cause of the fault. The fault self-diagnosis function can quickly and accurately detect the cause of the communication fault and provide a basis for fault recovery;

[0042] If the communication failure is caused by improper frequency selection, the communication unit will automatically start the adaptive algorithm to readjust the frequency. If it is a hardware failure, the communication unit will issue an alarm to remind the user to repair it. The fault recovery function can automatically take corresponding recovery measures according to the cause of the fault to ensure the reliability and stability of communication.

[0043] S9. Establish a priority system;

[0044] S901, setting priority;

[0045] According to different application scenarios and communication requirements, priorities are set for various environmental parameters and communication quality indicators, and a priority system with a priority formula is generated. The priority system can flexibly adjust the priorities of environmental parameters and communication quality indicators according to different application scenarios and communication requirements to meet different communication requirements;

[0046] S902, dynamic adjustment of priority;

[0047] In scenarios with high real-time requirements, the bit error rate may be prioritized over signal strength. When adjusting the communication frequency and power, the adaptive algorithm will give priority to high-priority indicators to ensure that key communication needs are met. The priority system can be dynamically adjusted according to actual conditions to adapt to different communication needs and environmental changes;

[0048] S10, data encryption and secure transmission;

[0049] S1001, data encryption;

[0050] In special working environments, the security of communication is extremely important. Advanced data encryption technology is used to ensure the secure transmission of communication data. Data encryption technology can encrypt communication data to prevent data from being stolen and tampered with.

[0051] S1002, data integrity check;

[0052] The communication unit can also perform integrity check on the transmitted data to prevent data tampering or loss. The integrity check technology can check the transmitted data to ensure the integrity and accuracy of the data;

[0053] S11, remote monitoring and management;

[0054] Through network connection, users can remotely monitor the operating status of the communication unit, including environmental parameters, communication quality, frequency and power adjustment. The remote monitoring function allows users to understand the operating status of the communication unit anytime and anywhere, and discover and solve problems in a timely manner. Users can also remotely manage and configure the communication unit, such as adjusting the sensitivity of the sensor, setting the communication mode and frequency range. The remote management function allows users to easily manage and configure the communication unit and improve work efficiency.

[0055] The present invention can automatically adjust the communication mode according to changes in the special working environment by accurately collecting environmental parameters, comprehensively evaluating the communication quality and flexibly adjusting the communication frequency, significantly improving the stability and reliability of communication, avoiding communication failures caused by environmental factors, and at the same time improving transmission efficiency, reducing transmission time and energy consumption, and solving the problems of unstable signals and low transmission efficiency in traditional communications under special environments.

[0056] Preferably, the acquisition formula is: environmental parameter set P = {T, H, E}, wherein T represents the temperature value, H represents the humidity value, and E represents the electromagnetic interference intensity value.

[0057] Preferably, the judgment formula is: if T∈[T min_A ,T max_A ] and H∈[H min_A ,H max_A ] and E∈[Emin_A ,E max_A ], then it is suitable for mode A communication; otherwise, it is not suitable;

[0058] Among them, T min_A and T max_A Respectively represent the minimum and maximum allowable values ​​of temperature in mode A;

[0059] H min_A and H max_A They represent the minimum and maximum permissible values ​​of humidity in mode A respectively;

[0060] E min_A and E max_A They respectively represent the minimum and maximum permissible values ​​of electromagnetic interference intensity under mode A.

[0061] Preferably, the evaluation formula is: communication quality index Q=αS+βBER+γR;

[0062] Among them, Q represents the communication quality index, S represents the signal strength value, BER represents the bit error rate, represents the transmission rate value, α, β, γ are weight coefficients, satisfying α+β+γ=1, and are adjusted according to different application scenarios.

[0063] Preferably, the adjustment formula is:

[0064] F new =F old +ΔF;

[0065] Among them, F new Indicates the adjusted frequency value, F old represents the frequency value before adjustment. ΔF is adjusted according to the change of communication quality index Q. Let Q old is the communication quality index before adjustment, Q new The adjusted communication quality index is:

[0066] When Q new >Q old When ΔF=λ(Q new -Q old ), where λ is a positive adjustment coefficient;

[0067] When Q new old When ΔF=-μ(Q old -Q new ), where μ is a positive adjustment coefficient.

[0068] Preferably, the learning formula is: Let the environmental parameter set P = {T, H, E}, the optimal communication frequency is F optimal , the function is obtained through machine learning algorithm: ​

[0069] F optimal =f{T,H,E}=aT 2 +bT+cH 2 +dH+eE 2 +fE+g;

[0070] Among them, a, b, c, d, e, f, and g are coefficients obtained through machine learning training.

[0071] Preferably, the power adjustment formula is:

[0072] P tx_new =p tx_old +ΔP tx ;

[0073] Among them, P tx_new Indicates the adjusted transmit power value, P tx_old Indicates the transmit power value before adjustment, ΔP tx According to the environmental parameters and the communication quality index Q, let S old is the communication quality index before adjustment, S new The adjusted communication quality index is:

[0074] When the environmental disturbance is large or S new old When ΔP tx =η(S old -S new ), where η is a positive adjustment coefficient;

[0075] When the environmental disturbance is small and S new >S old When ΔP tx =-θ(S new -S old ), where θ is a positive adjustment coefficient.

[0076] Preferably, the S7 multi-sensor fusion further comprises the following steps:

[0077] S701, comprehensive acquisition of environmental information;

[0078] In order to fully understand the special working environment, multi-sensor fusion technology is used to integrate and analyze different types of sensor data to obtain more comprehensive and accurate environmental information;

[0079] S702, sensor expansion;

[0080] In addition to temperature, humidity and electromagnetic interference intensity sensors, it also integrates air pressure sensors, vibration sensors and other types of sensors to provide more environmental information and help the communication unit better adapt to special working environments;​

[0081] S702, multi-sensor data fusion analysis;

[0082] Through comprehensive analysis of data from multiple sensors, environmental conditions can be judged more accurately, providing richer information for the adaptive algorithm. The communication unit will use advanced data analysis algorithms and fusion formulas to fuse and analyze data from multiple sensors, extract useful information and rules, and provide more accurate and comprehensive environmental information for the adaptive algorithm.

[0083] Preferably, the fusion formula assumes that the environmental parameters collected by different sensors are:

[0084] P1={T1,H1,E1}, P2={T2,H2,E2},......,P n ={T n ,H n ,E n};

[0085] The comprehensive environmental parameters are:

[0086]

[0087] Preferably, the priority formula is: assuming that the environmental parameter set P = {T, H, E}, the communication quality index is Q, and the priority index is:

[0088] P priority =h(P,Q)=δ1T+δ2H+δ3E+δ4Q;

[0089] Among them, δ1, δ2, δ3, and δ4 are weight coefficients, which are adjusted according to different application scenarios and requirements.

[0090] Compared with the prior art, the present invention has the following beneficial effects:

[0091] 1. The present invention can automatically adjust the communication mode according to the changes in the special working environment by accurately collecting environmental parameters, comprehensively evaluating the communication quality and flexibly adjusting the communication frequency, significantly improving the stability and reliability of communication, avoiding communication failures caused by environmental factors, and at the same time improving transmission efficiency, reducing transmission time and energy consumption, thus solving the problems of unstable signals and low transmission efficiency in traditional communications under special environments.

[0092] 2. The present invention is also suitable for various special working environments, such as high temperature, high humidity, strong electromagnetic interference, etc., through its powerful adaptability and intelligent optimization. The intelligent learning module can accurately predict the optimal communication frequency, and the multi-sensor fusion technology provides more comprehensive and accurate environmental information. The dynamic power adjustment function automatically adjusts the transmission power according to the environment and communication quality. The fault self-diagnosis and recovery function ensures communication reliability. A priority system is established to meet the needs of different scenarios, so that the communication unit can quickly adapt to different special working environments and continuously optimize communication performance.

[0093] 3. The present invention also ensures communication security through convenient management and security protection, data encryption and secure transmission, prevents information leakage and tampering, and the remote monitoring and management functions are convenient and practical. Users can understand the operating status of the communication unit anytime and anywhere, and flexibly configure and manage it to improve work efficiency, providing all-round security protection and convenient management for communications in special working environments. DETAILED DESCRIPTION

[0094] The present invention relates to a dual-mode communication unit frequency modulation method based on an adaptive algorithm, comprising the following steps:

[0095] S1. Collect and analyze environmental parameters;

[0096] S101, collection of special working environment parameters;

[0097] The temperature (T), humidity (H), and electromagnetic interference intensity (E) parameters in special working environments are collected through a variety of high-precision sensors. The sensors are calibrated to accurately sense subtle changes in the environment, and the collected formulas are used to provide a basis for the frequency adjustment of the communication unit.

[0098] The collection formula is: environmental parameter set P = {T, H, E}, where T represents the temperature value, H represents the humidity value, and E represents the electromagnetic interference intensity value;

[0099] S102, in-depth analysis of environmental parameters;

[0100] Conduct an in-depth analysis of the collected environmental parameters and use the judgment formula to determine whether the current environment is suitable for Mode A communication. During the analysis, the communication unit will use advanced data analysis algorithms to compare the collected environmental parameters with the preset applicable range of Mode A. If the environmental parameters are within the applicable range of Mode A, Mode A will continue to be used for communication; if the environmental parameters are beyond the applicable range of Mode A, proceed to the next step.

[0101] The judgment formula is: If T∈[T min_A ,T max_A ] and H∈[H min_A ,H max_A ] and E∈[E min_A ,Emax_A ], then it is suitable for mode A communication; otherwise, it is not suitable;

[0102] Among them, T min_A and T max_A Respectively represent the minimum and maximum allowable values ​​of temperature in mode A;

[0103] H min_A and H max_A They represent the minimum and maximum permissible values ​​of humidity in mode A respectively;

[0104] E min_A and E max_A They represent the minimum and maximum permissible values ​​of electromagnetic interference intensity under mode A respectively;

[0105] S2. Evaluate communication quality;

[0106] S201, automatic mode switching;

[0107] When communication in mode A is affected, the communication unit automatically switches to mode B. The switching process is fast and smooth to ensure that communication will not be interrupted. During the switching, the communication unit will record the reason and time of the switching for subsequent analysis and optimization.

[0108] S202, comprehensive assessment of communication quality;

[0109] Comprehensively evaluate the communication quality of mode B. The evaluation indicators include signal strength (S), bit error rate (BER), and transmission rate (R). To ensure the accuracy of the evaluation, the communication unit will monitor the changes in signal strength in real time, count the frequency of bit error rate, and measure the transmission rate. By evaluating the above indicators based on the evaluation formula, we can understand the communication effect of mode B in the current environment and provide a reference for subsequent frequency adjustment.

[0110] The evaluation formula is: Communication quality index Q = αS + βBER + γR;

[0111] Among them, Q represents the communication quality index, S represents the signal strength value, BER represents the bit error rate, represents the transmission rate value, α, β, γ are weight coefficients, satisfying α+β+γ=1, and are adjusted according to different application scenarios;

[0112] S3, adjust the communication frequency;

[0113] S301, adaptive algorithm;

[0114] According to the evaluation results, the adaptive algorithm automatically adjusts the frequency (F) of the communication unit based on the adjustment formula. The adjustment methods are flexible and diverse. The frequency can be gradually adjusted within a certain range to find the best communication frequency, or it can quickly switch to a specific frequency according to the preset frequency adjustment strategy. During the frequency adjustment process, the communication unit will continuously monitor the communication quality and adjust the speed and direction of the frequency adjustment in real time according to the changes in the communication quality.

[0115] The adjustment formula is: F new =F old +ΔF;

[0116] Among them, F new Indicates the adjusted frequency value, F old represents the frequency value before adjustment. ΔF is adjusted according to the change of communication quality index Q. Let Q old is the communication quality index before adjustment, Q new The adjusted communication quality index is:

[0117] When Q new >Q old When ΔF=λ(Q new -Q old ), where λ is a positive adjustment coefficient;

[0118] When Q new old When ΔF=-μ(Q old -Q new ), where μ is a positive adjustment coefficient;

[0119] S302, frequency adjustment strategy;

[0120] In the process of adjusting the frequency, the communication unit will also take into account the changes in the surrounding environment and the influence of interference from other communication devices. If the above factors affect the communication quality, the communication unit will adjust the frequency adjustment strategy in time to ensure that the best frequency that can meet the communication needs is found;

[0121] S4, real-time monitoring;

[0122] S401, collation and analysis of monitoring data;

[0123] After adjusting the frequency, the communication unit continues to monitor the environmental parameters and communication quality in real time. The monitoring process is continuous and will not be interrupted by other operations of the communication unit. The communication unit will regularly organize and analyze the monitored data to timely detect changes in environmental parameters and communication quality;

[0124] S402, frequency adjustment optimization;

[0125] ​If the environmental parameters change or the communication quality decreases, the adaptive algorithm will start again and readjust the communication frequency. In the process of readjusting the frequency, the communication unit will draw on the previous adjustment experience to speed up the adjustment and improve the accuracy of the adjustment;

[0126] The present invention effectively solves the problems of traditional communication in special environments. By accurately collecting environmental parameters, comprehensively evaluating communication quality, and flexibly adjusting communication frequency, the present invention can automatically adjust the communication mode according to changes in the special working environment, significantly improve the stability and reliability of communication, avoid communication failures caused by environmental factors, and at the same time improve transmission efficiency, reduce transmission time and energy consumption, and solve the problems of unstable signals and low transmission efficiency of traditional communication in special environments;

[0127] S5, intelligent learning model;

[0128] S501, communication data storage;

[0129] During operation, the communication unit continuously accumulates communication data in different environments. These data include environmental parameters, communication mode, frequency, and communication quality information. Data accumulation is a continuous process. The communication unit will record and store each communication data for subsequent analysis and learning.

[0130] S502, deep learning model;

[0131] Through the intelligent learning model, the data is deeply analyzed and learned based on the learning formula, and the mapping relationship between environmental parameters and optimal communication frequency is established. The intelligent learning module will use advanced machine learning algorithms to analyze and process a large amount of communication data and extract useful information and rules from it. With the continuous accumulation of data, the communication unit can more accurately predict the optimal communication frequency in a specific environment.

[0132] The learning formula is: Let the environmental parameter set P = {T, H, E}, and the optimal communication frequency be F optimal , the function is obtained through machine learning algorithm:

[0133] F optimal =f{T,H,E}=aT 2 +bT+cH 2 +dH+eE 2 +fE+g;

[0134] Among them, a, b, c, d, e, f, and g are coefficients obtained through machine learning training;

[0135] S503, predicting the optimal communication frequency range;

[0136] In practical applications, the intelligent learning module can predict the possible optimal communication frequency range based on historical data, thereby speeding up the frequency modulation speed. The intelligent learning module will predict the most likely optimal communication frequency range based on the current environmental parameters and historical data. When adjusting the frequency, the communication unit can search within this range first, thereby greatly speeding up the frequency modulation speed.

[0137] S6, dynamic power adjustment;

[0138] S601, adjusting the transmission power in real time according to environmental parameters and communication quality;

[0139] In addition to adjusting the communication frequency, the transmission power (P tx ), dynamic power adjustment is a real-time process. The communication unit will adjust the transmission power in real time according to the changes in environmental parameters and communication quality and based on the power adjustment formula;

[0140] The power adjustment formula is:

[0141] P tx_new =P tx_old +ΔP tx ;

[0142] Among them, P tx_new Indicates the adjusted transmit power value, P tx_old Indicates the transmit power value before adjustment, ΔP tx According to the environmental parameters and the communication quality index Q, let S old is the communication quality index before adjustment, S new The adjusted communication quality index is:

[0143] When the environmental disturbance is large or S new old When ΔP tx =η(S old -S new ), where η is a positive adjustment coefficient;

[0144] When the environmental disturbance is small and S new >S old When ΔP tx = -θ(S new -S old ), where θ is a positive adjustment coefficient;

[0145] S602, automatically adjusting the transmission power according to environmental interference;

[0146] ​Under the premise of ensuring communication quality, reducing the transmission power can reduce energy consumption and extend the working time of the communication unit. When the environmental interference is large, the transmission power can be appropriately increased to enhance the signal strength and improve the reliability of communication. The communication unit will automatically adjust the transmission power according to the degree of environmental interference and the requirements of communication quality to achieve the best communication effect;

[0147] S7, multi-sensor fusion;

[0148] S701, comprehensive acquisition of environmental information;

[0149] In order to fully understand the special working environment, multi-sensor fusion technology is used to integrate and analyze different types of sensor data to obtain more comprehensive and accurate environmental information;

[0150] S702, sensor expansion;

[0151] In addition to temperature, humidity and electromagnetic interference intensity sensors, it also integrates air pressure sensors, vibration sensors and other types of sensors to provide more environmental information and help the communication unit better adapt to special working environments;

[0152] S702, multi-sensor data fusion analysis;

[0153] Through comprehensive analysis of multiple sensor data, the environmental conditions can be judged more accurately, providing more abundant information for the adaptive algorithm. The communication unit will use advanced data analysis algorithms and fusion formulas to fuse and analyze multiple sensor data, extract useful information and rules from them, and provide more accurate and comprehensive environmental information for the adaptive algorithm.

[0154] The fusion formula assumes that the environmental parameters collected by different sensors are:

[0155] P1={T1,H1,E1}, P2={T2,H2,E2},......,P n ={T n ,H n ,E n};

[0156] The comprehensive environmental parameters are:

[0157]

[0158] The present invention has strong adaptability and intelligent optimization. It is suitable for various special working environments, such as high temperature, high humidity, strong electromagnetic interference, etc. The intelligent learning module can accurately predict the optimal communication frequency, the multi-sensor fusion technology provides more comprehensive and accurate environmental information, the dynamic power adjustment function automatically adjusts the transmission power according to the environment and communication quality, the fault self-diagnosis and recovery function ensures communication reliability, and establishes a priority system to meet the needs of different scenarios, so that the communication unit can quickly adapt to different special working environments and continuously optimize communication performance;

[0159] S8, fault self-diagnosis and recovery;

[0160] The communication unit has a fault self-diagnosis function. When a communication fault occurs, it can automatically detect the cause of the fault. The fault self-diagnosis function can quickly and accurately detect the cause of the communication fault and provide a basis for fault recovery;

[0161] If the communication failure is caused by improper frequency selection, the communication unit will automatically start the adaptive algorithm to readjust the frequency. If it is a hardware failure, the communication unit will issue an alarm to remind the user to repair it. The fault recovery function can automatically take corresponding recovery measures according to the cause of the fault to ensure the reliability and stability of communication.

[0162] S9. Establish a priority system;

[0163] S901, setting priority;

[0164] According to different application scenarios and communication requirements, priorities are set for various environmental parameters and communication quality indicators, and a priority system with a priority formula is generated. The priority system can flexibly adjust the priorities of environmental parameters and communication quality indicators according to different application scenarios and communication requirements to meet different communication requirements;

[0165] Priority formula: Let the environmental parameter set P = {T, H, E}, the communication quality index is Q, and the priority index is:

[0166] P priority =h(P,Q)=δ1T+δ2H+δ3E+δ4Q;

[0167] Among them, δ1, δ2, δ3, and δ4 are weight coefficients, which are adjusted according to different application scenarios and requirements;

[0168] S902, dynamic adjustment of priority;

[0169] In scenarios with high real-time requirements, the bit error rate may be prioritized over signal strength. When adjusting the communication frequency and power, the adaptive algorithm will give priority to high-priority indicators to ensure that key communication needs are met. The priority system can be dynamically adjusted according to actual conditions to adapt to different communication needs and environmental changes;

[0170] S10, data encryption and secure transmission;

[0171] S1001, data encryption;

[0172] In special working environments, the security of communication is extremely important. Advanced data encryption technology is used to ensure the secure transmission of communication data. Data encryption technology can encrypt communication data to prevent data from being stolen and tampered with.

[0173] S1002, data integrity check;

[0174] The communication unit can also perform integrity check on the transmitted data to prevent data tampering or loss. The integrity check technology can check the transmitted data to ensure the integrity and accuracy of the data;

[0175] S11, remote monitoring and management;

[0176] Through network connection, users can remotely monitor the operating status of the communication unit, including environmental parameters, communication quality, frequency and power adjustment. The remote monitoring function allows users to understand the operating status of the communication unit anytime and anywhere, and discover and solve problems in a timely manner. Users can also remotely manage and configure the communication unit, such as adjusting the sensitivity of the sensor, setting the communication mode and frequency range. The remote management function allows users to easily manage and configure the communication unit and improve work efficiency.

[0177] The present invention provides convenient management and security. Data encryption and secure transmission ensure communication security and prevent information leakage and tampering. The remote monitoring and management functions are convenient and practical. Users can understand the operating status of the communication unit anytime and anywhere, and perform flexible configuration and management to improve work efficiency, providing all-round security and convenient management for communications in special working environments.

[0178] The embodiments of the present invention disclose preferred embodiments, but are not limited thereto. A person skilled in the art can easily understand the spirit of the present invention based on the above embodiments and make different extensions and changes. However, as long as they do not deviate from the spirit of the present invention, they are all within the protection scope of the present invention.

Claims

1. A frequency modulation method for a dual-mode communication unit based on an adaptive algorithm, characterized in that: The following steps are involved: S1. Collect and analyze environmental parameters; S101, collection of special working environment parameters; The temperature (T), humidity (H), and electromagnetic interference intensity (E) parameters in special working environments are collected through a variety of high-precision sensors. The sensors are calibrated to accurately sense subtle changes in the environment, and the collected formulas are used to provide a basis for the frequency adjustment of the communication unit. S102, in-depth analysis of environmental parameters; Conduct an in-depth analysis of the collected environmental parameters and use the judgment formula to determine whether the current environment is suitable for Mode A communication. During the analysis, the communication unit will use advanced data analysis algorithms to compare the collected environmental parameters with the preset applicable range of Mode A. If the environmental parameters are within the applicable range of Mode A, Mode A will continue to be used for communication; if the environmental parameters are beyond the applicable range of Mode A, proceed to the next step. S2. Evaluate communication quality; S201, automatic mode switching; When communication in mode A is affected, the communication unit automatically switches to mode B. The switching process is fast and smooth to ensure that communication will not be interrupted. During the switching, the communication unit will record the reason and time of the switching for subsequent analysis and optimization. S202, comprehensive assessment of communication quality; Comprehensively evaluate the communication quality of mode B. The evaluation indicators include signal strength (S), bit error rate (BER), and transmission rate (R). To ensure the accuracy of the evaluation, the communication unit will monitor the changes in signal strength in real time, count the frequency of bit error rate, and measure the transmission rate. By evaluating the above indicators based on the evaluation formula, we can understand the communication effect of mode B in the current environment and provide a reference for subsequent frequency adjustment. S3, adjust the communication frequency; S301, adaptive algorithm; According to the evaluation results, the adaptive algorithm automatically adjusts the frequency (F) of the communication unit based on the adjustment formula. The adjustment methods are flexible and diverse. The frequency can be gradually adjusted within a certain range to find the best communication frequency, or it can quickly switch to a specific frequency according to the preset frequency adjustment strategy. During the frequency adjustment process, the communication unit will continuously monitor the communication quality and adjust the speed and direction of the frequency adjustment in real time according to the changes in the communication quality. S302, frequency adjustment strategy; In the process of adjusting the frequency, the communication unit will also take into account the changes in the surrounding environment and the influence of interference from other communication devices. If the above factors affect the communication quality, the communication unit will adjust the frequency adjustment strategy in time to ensure that the best frequency that can meet the communication needs is found; S4, real-time monitoring; S401, collation and analysis of monitoring data; After adjusting the frequency, the communication unit continues to monitor the environmental parameters and communication quality in real time. The monitoring process is continuous and will not be interrupted by other operations of the communication unit. The communication unit will regularly organize and analyze the monitored data to timely detect changes in environmental parameters and communication quality; S402, frequency adjustment optimization; If the environmental parameters change or the communication quality decreases, the adaptive algorithm will start again and readjust the communication frequency. In the process of readjusting the frequency, the communication unit will draw on the previous adjustment experience to speed up the adjustment and improve the accuracy of the adjustment; S5, intelligent learning model; S501, communication data storage; During operation, the communication unit continuously accumulates communication data in different environments. These data include environmental parameters, communication mode, frequency, and communication quality information. Data accumulation is a continuous process. The communication unit will record and store each communication data for subsequent analysis and learning. S502, deep learning model; Through the intelligent learning model, the data is deeply analyzed and learned based on the learning formula, and the mapping relationship between environmental parameters and optimal communication frequency is established. The intelligent learning module will use advanced machine learning algorithms to analyze and process a large amount of communication data and extract useful information and rules from it. With the continuous accumulation of data, the communication unit can more accurately predict the optimal communication frequency in a specific environment. S503, predicting the optimal communication frequency range; In practical applications, the intelligent learning module can predict the possible optimal communication frequency range based on historical data, thereby speeding up the frequency modulation speed. The intelligent learning module will predict the most likely optimal communication frequency range based on the current environmental parameters and historical data. When adjusting the frequency, the communication unit can search within this range first, thereby greatly speeding up the frequency modulation speed. S6, dynamic power adjustment; S601, adjusting the transmission power in real time according to environmental parameters and communication quality; In addition to adjusting the communication frequency, the transmission power (P tx ), dynamic power adjustment is a real-time process. The communication unit will adjust the transmission power in real time according to the changes in environmental parameters and communication quality and based on the power adjustment formula; S602, automatically adjusting the transmission power according to environmental interference; Under the premise of ensuring communication quality, reducing the transmission power can reduce energy consumption and extend the working time of the communication unit. When the environmental interference is large, the transmission power can be appropriately increased to enhance the signal strength and improve the reliability of communication. The communication unit will automatically adjust the transmission power according to the degree of environmental interference and the requirements of communication quality to achieve the best communication effect; S7, multi-sensor fusion; Adopting multi-sensor fusion technology, different types of sensor data are integrated and analyzed. In addition to temperature, humidity and electromagnetic interference intensity sensors, air pressure sensors, vibration sensors and other types of sensors are also integrated. Through comprehensive analysis of multiple sensor data, environmental conditions can be judged more accurately, providing more abundant information for the adaptive algorithm. The communication unit will use advanced data analysis algorithms and fusion formulas to fuse and analyze multiple sensor data, extract useful information and rules from them, and provide more accurate and comprehensive environmental information for the adaptive algorithm. S8, fault self-diagnosis and recovery; The communication unit has a fault self-diagnosis function. When a communication fault occurs, it can automatically detect the cause of the fault. The fault self-diagnosis function can quickly and accurately detect the cause of the communication fault and provide a basis for fault recovery; If the communication failure is caused by improper frequency selection, the communication unit will automatically start the adaptive algorithm to readjust the frequency. If it is a hardware failure, the communication unit will issue an alarm to remind the user to repair it. The fault recovery function can automatically take corresponding recovery measures according to the cause of the fault to ensure the reliability and stability of communication. S9. Establish a priority system; S901, setting priority; According to different application scenarios and communication requirements, priorities are set for various environmental parameters and communication quality indicators, and a priority system with a priority formula is generated. The priority system can flexibly adjust the priorities of environmental parameters and communication quality indicators according to different application scenarios and communication requirements to meet different communication requirements; S902, dynamic adjustment of priority; In scenarios with high real-time requirements, the bit error rate may be prioritized over signal strength. When adjusting the communication frequency and power, the adaptive algorithm will give priority to high-priority indicators to ensure that key communication needs are met. The priority system can be dynamically adjusted according to actual conditions to adapt to different communication needs and environmental changes; S10, data encryption and secure transmission; S1001, data encryption; In special working environments, the security of communication is extremely important. Advanced data encryption technology is used to ensure the secure transmission of communication data. Data encryption technology can encrypt communication data to prevent data from being stolen and tampered with. S1002, data integrity check; The communication unit can also perform integrity check on the transmitted data to prevent data tampering or loss. The integrity check technology can check the transmitted data to ensure the integrity and accuracy of the data; S11, remote monitoring and management; Through network connection, users can remotely monitor the operating status of the communication unit, including environmental parameters, communication quality, frequency and power adjustment. The remote monitoring function allows users to understand the operating status of the communication unit anytime and anywhere, and discover and solve problems in a timely manner. Users can also remotely manage and configure the communication unit, such as adjusting the sensitivity of the sensor, setting the communication mode and frequency range. The remote management function allows users to easily manage and configure the communication unit and improve work efficiency.

2. A dual-mode communication unit frequency modulation method based on an adaptive algorithm according to claim 1, characterized in that: The acquisition formula is: environmental parameter set P = {T, H, E}, where T represents the temperature value, H represents the humidity value, and E represents the electromagnetic interference intensity value.

3. A dual-mode communication unit frequency modulation method based on an adaptive algorithm according to claim 1, characterized in that: The judgment formula is: if T∈[T min_A , T max_A ] and H∈[H min_A , H max_A ] and E∈[E min_A , E max_A ], then it is suitable for mode A communication; otherwise, it is not suitable; Among them, T min_A and T max_A Respectively represent the minimum and maximum allowable values ​​of temperature in mode A; H min_A and H max_A They represent the minimum and maximum permissible values ​​of humidity in mode A respectively; E min_A and E max_A They respectively represent the minimum and maximum permissible values ​​of electromagnetic interference intensity under mode A.

4. The frequency modulation method of a dual-mode communication unit based on an adaptive algorithm according to claim 1, characterized in that: The evaluation formula is: communication quality index Q = αS + βBER + yR; Among them, Q represents the communication quality index, S represents the signal strength value, BER represents the bit error rate, represents the transmission rate value, α, β, γ are weight coefficients, satisfying α+β+γ=1, and are adjusted according to different application scenarios.

5. The frequency modulation method of a dual-mode communication unit based on an adaptive algorithm according to claim 1, characterized in that: The adjustment formula is: F new =F old +ΔF; Among them, F new Indicates the adjusted frequency value, F old represents the frequency value before adjustment. ΔF is adjusted according to the change of communication quality index Q. Let Q old is the communication quality index before adjustment, Q new The adjusted communication quality index is: When Q new >Q old When ΔF=λ(Q new -Q old ), where λ is a positive adjustment coefficient; When Q new <Q old When ΔF=-μ(Q old -Q new ), where μ is a positive adjustment coefficient.

6. A dual-mode communication unit frequency modulation method based on an adaptive algorithm according to claim 1, characterized in that: The learning formula is: Let the environmental parameter set P = {T, H, E}, the optimal communication frequency be F optimal , the function is obtained through machine learning algorithm: F optimal =f{T,H,E}=aT 2 +bT+cH 2 +dH+eE 2 +fE+g; Among them, a, b, c, d, e, f, and g are coefficients obtained through machine learning training.

7. A dual-mode communication unit frequency modulation method based on an adaptive algorithm according to claim 1, characterized in that: The power adjustment formula is: P tx_new =P tx_old +ΔP tx ; Among them, P tx_new Indicates the adjusted transmit power value, P tx_old Indicates the transmit power value before adjustment, ΔP tx According to the environmental parameters and the communication quality index Q, let S old is the communication quality index before adjustment, S new The adjusted communication quality index is: When the environmental disturbance is large or S new <S old When ΔP tx =η(S old -S new ), where η is a positive adjustment coefficient; When the environmental disturbance is small and S new >S old When ΔPt x = -θ(S new -S old ), where θ is a positive adjustment coefficient.

8. The frequency modulation method of a dual-mode communication unit based on an adaptive algorithm according to claim 1, characterized in that: The S7 multi-sensor fusion further comprises the following steps: S701, comprehensive acquisition of environmental information; In order to fully understand the special working environment, multi-sensor fusion technology is used to integrate and analyze different types of sensor data to obtain more comprehensive and accurate environmental information; S702, sensor expansion; In addition to temperature, humidity and electromagnetic interference intensity sensors, it also integrates air pressure sensors, vibration sensors and other types of sensors to provide more environmental information and help the communication unit better adapt to special working environments; S702, multi-sensor data fusion analysis; Through comprehensive analysis of data from multiple sensors, environmental conditions can be judged more accurately, providing richer information for the adaptive algorithm. The communication unit will use advanced data analysis algorithms and fusion formulas to fuse and analyze data from multiple sensors, extract useful information and rules, and provide more accurate and comprehensive environmental information for the adaptive algorithm.

9. A dual-mode communication unit frequency modulation method based on an adaptive algorithm according to claim 8, characterized in that: The fusion formula assumes that the environmental parameters collected by different sensors are: P1={T1,H1,E1},P2={T2,H2,E2},......,P n ={T n ,H n ,E n }; The comprehensive environmental parameters are:

10. The frequency modulation method of a dual-mode communication unit based on an adaptive algorithm according to claim 1, characterized in that: The priority formula is: suppose the environmental parameter set P = {T, H, E}, the communication quality index is Q, and the priority index is: P priority =h(P,Q)=δ1T+δ2H+δ3E+δ4Q; Among them, δ1, δ2, δ3, and δ4 are weight coefficients, which are adjusted according to different application scenarios and requirements.

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