CN117439687B - Dual-mode communication method, system and device based on HPLC and HRF - Google Patents
Dual-mode communication method, system and device based on HPLC and HRF Download PDFInfo
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Abstract
The invention discloses a method based onHPLCAndHRFthe dual-mode communication method, system and device relate to the technical field of power grid communication, and are used for detecting the current communication state of a communication module and constructing a communication state set, generating a communication state coefficient by the communication state set, and carrying out the communication on the communication module according to the relation between the communication state coefficient and a critical threshold valueHPLCChannel and method for transmitting dataHRFSwitching channels; after the communication mode of the communication module is adjusted, constructing a regression equation, generating an influence coefficient by the corresponding regression coefficient, and carrying out adaptive processing on the communication module according to the relation between the influence coefficient and an influence threshold; and predicting the running state of the communication module by using the trained communication module running model, performing targeted optimization on the communication module according to the prediction result, and sending an alarm instruction if the optimization result does not reach the expectation. The communication module has certain adaptability under different communication conditions, so that the usability of the communication module is improved.
Description
Technical Field
The invention relates to the technical field of power grid communication, in particular to a power grid communication-based power grid communication system HPLCAndHRFa dual mode communication method, a system and a device.
Background
When the ammeter is communicated to the outside, a communication module is needed, wherein the communication module is more commonly usedHPLCCommunication moduleHRFCommunication modules, i.e.HPLCChannel and method for transmitting dataHRFA channel.HPLCThe communication module is a power line carrier communication module, and the advantages of the communication module include high speed, high reliability, high anti-interference capability, long communication distance and extremely strong confidentiality. The module adoptsHPLCHigh-speed carrier chip, internal integrated 32-bit processor, adoptsBPSKDigital modulation-demodulation mode transmission, built-in coupling circuitPAA power amplifier.HRFThe communication module is widely applied to the fields of intelligent power grids, industrial automation, security monitoring, logistics tracking and the like.
By usingHRFAnd the communication module can realize wireless connection and data transmission between devices and improve the working efficiency and convenience. At the same time, the method comprises the steps of,HRFthe communication module can also be interconnected with other communication modules to formA more bulky and complex communication system is built.
In the application publication number CN116527430A is disclosed aHPLCAndHRFthe access method of the dual-mode communication network comprises the following steps: acquiring ammeter information and importing the ammeter information into a master station; the system is powered on, and a dual-mode module channel in the ammeter is selected: the dual-mode module sends a network access request to the concentrator, and the concentrator reports information of the dual-mode module sending the network access request and a serial number of the concentrator to the master station: and (3) carrying out network access decision of the dual-mode module in the ammeter through the master station, thereby completing network access.
The application solves the technical problem of how to accurately and effectively perform unified management on network access of the ammeter nodes; however, after the communication module of the electric meter is used for a long time, various performances are reduced to a certain extent, under the condition that the data is lost and delayed seriously when the communication module exchanges data with the outside, the display of the data on the electric meter is distorted and delayed to a certain extent when the data is processed on the basis, and therefore, certain interference and influence are brought to the use of the electric meter or similar electric meters, three-phase meters and the like.
In the existing method, the problem is usually solved by continuously switching the communication mode to change the channel, but the frequent switching of the communication channel can improve the data communication quality, but the adaptability between the communication module and the actual use scene still has certain defects, and the running risk of the communication module is higher.
To this end, the invention provides a method based onHPLCAndHRFa dual mode communication method, a system and a device.
Disclosure of Invention
(one) solving the technical problems
Aiming at the defects of the prior art, the invention provides a novel base onHPLCAnd HRFDetecting the current communication state of a communication module, constructing a communication state set, generating a communication state coefficient by the communication state set, and carrying out communication on the communication module according to the relation between the communication state coefficient and a critical threshold valueIn the inner partHPLCChannel and method for transmitting dataHRFSwitching channels; after the communication mode of the communication module is adjusted, constructing a regression equation, generating an influence coefficient by the corresponding regression coefficient, and carrying out adaptive processing on the communication module according to the relation between the influence coefficient and an influence threshold; and predicting the running state of the communication module by using the trained communication module running model, performing targeted optimization on the communication module according to the prediction result, and sending an alarm instruction if the optimization result does not reach the expectation. The communication module has certain adaptability under different communication conditions, so that the usability of the communication module is improved, and the technical problem in the background technology is solved.
(II) technical scheme
In order to achieve the above purpose, the invention is realized by the following technical scheme:
based onHPLCAndHRFthe dual-mode communication method of (1) includes constructing a communication condition set from communication condition data of a communication module, and generating a communication condition coefficient from the communication condition set If the obtained communication condition coefficientExceeding a condition threshold value, and sending an early warning instruction to the outside;
after receiving the early warning instruction, detecting the current communication state of the communication module, constructing a communication state set, and generating a communication state coefficient by the communication state setAccording to the communication state coefficient->Relationship with critical threshold, for communication moduleHPLCChannel and method for transmitting dataHRFSwitching channels; wherein the communication condition coefficient->The generation mode of the (c) is as follows: amount of data lossToNumber of timesAccording to the delay amountLoPerforming linear normalization processing, and mapping corresponding data value to interval +.>And then according to the following mode: />
Wherein,nthe number of the working periods is a positive integer greater than 1,the method comprises the steps of carrying out a first treatment on the surface of the Weight coefficient:，/>and->Said->Is a qualified standard value of data loss amount, +.>Is a qualified standard value of the data delay amount;
after the communication mode of the communication module is adjusted, a regression equation is constructed by multiple regression analysis, and an influence coefficient is generated by the corresponding regression coefficientAccording to influence coefficient->The relation with influencing the threshold value, make adaptive processing to the communication module;
and predicting the running state of the communication module by using the trained communication module running model, performing targeted optimization on the communication module according to the prediction result, and sending an alarm instruction if the optimization result does not reach the expectation.
Further, in the working period, the data loss amount of the communication module when exchanging data with the outside is obtainedToThe method comprises the steps of carrying out a first treatment on the surface of the When data communication is generated in a working period, if communication delay exists when data is received, the data delay amount is generatedLoThe method comprises the steps of carrying out a first treatment on the surface of the The continuous data loss amountToData delay amountLoSummarizing to generate a communication condition set of the communication module.
Further, signal stability in a plurality of detection periods is continuously obtainedQnRate stabilityQuSummarizing and constructing a communication state set of the communication module; wherein the communication state coefficientThe acquisition method of (1) is as follows: stability to signalsQnRate stabilityQuPerforming linear normalization processing, and mapping corresponding data value to interval +.>And then according to the following mode:
wherein,is a positive integer greater than 1, +.>Which is the number of detection cycles; weight coefficient:，/>and->Said->Is the mean value of the signal stability, +.>Is the average of the rate stability.
Further, from the pre-built communication protocol libraryHPLCChannel and method for transmitting dataHRFChannel matching corresponding communication protocol; according to the communication state coefficientThe distribution of the two communication modes is switched, and the specific mode is as follows:
if the acquired communication state coefficient Below a critical threshold, such thatHPLCThe channel enters a communication state, if not higher than the communication state, the channel is made toHRFThe channel enters a communication state; wherein the duration of the communication state and the communication state coefficientThe difference value between the two threshold values is positively correlated; and after the communication mode is selected, packaging and transmitting the data to be transmitted.
Further, atHPLCChannel and method for transmitting dataHRFAfter several times of switching among channels, the acquired data loss amount is obtainedToData delay amountLoAs an independent variable, by a communication state coefficientAs a dependent variable, performing multiple linear regression analysis to generate a target regression equation; determining regression coefficients of the independent variables from the target regression equation, and acquiring communication condition versus communication state coefficients from the regression coefficients>Influence coefficient of->The concrete mode is as follows: the regression coefficient is used as an influence factor to respectively obtain the data lossToData delay amountLoInfluence factor of->Is->According to the following formula:
weight coefficient:，/>the specific value of which is set by the user adjustment.
Further, if the coefficient of influenceThe communication module is cooled below a preset influence threshold value, and if the influence coefficient is + ->Not lower than a preset influence threshold, and using a target regression equation to +. >Making predictions to obtain communication state coefficients +.>Reaching a communication condition for which a state is expected; and correspondingly adjusting the current communication condition of the communication module, wherein the adjusted communication condition is used as a target communication condition.
Further, use is made ofBpAfter the neural network builds an initial model, training and testing the initial model, taking the trained initial model as a communication module operation model, taking a target communication condition as a test condition, using the trained communication module operation model to conduct predictive analysis on the operation of the communication module, predicting and obtaining operation data of the communication module, performing feature recognition on the prediction data, and performing feature recognition on the obtained feature parametersAnd summarizing a plurality of optimized features to optimize the features, and constructing an optimized feature set.
Further, taking optimization of the communication module as a target word, and constructing an optimized knowledge graph of the communication module; according to the correspondence between the optimization features and the optimization schemes, matching a corresponding optimization scheme from the optimization knowledge graph of the communication module, and executing the optimization scheme by the communication module;
after a plurality of observation periods, a plurality of communication state coefficients are continuously acquiredOrderly arranged along a time axis to acquire a communication state data column; and carrying out trend analysis on the communication state data sequence, acquiring corresponding relative strength indexes, and sending out an alarm instruction if the relative strength indexes do not fall into a preset range.
Based onHPLCAndHRFa dual mode communication system of (1), comprising:
the early warning unit constructs a communication condition set by the communication condition data of the communication module, further generates a communication condition coefficient by the communication condition set, and sends an early warning instruction to the outside if the acquired communication condition coefficient exceeds a condition threshold value;
the switching unit is used for detecting the current communication state of the communication module and constructing a communication state set after receiving the early warning instruction, generating a communication state coefficient by the communication state set, and carrying out the relation between the communication state coefficient and a critical threshold value on the communication moduleHPLCChannel and method for transmitting dataHRFSwitching channels;
the analysis unit is used for constructing a regression equation after adjusting the communication mode of the communication module, generating an influence coefficient by the corresponding regression coefficient, and carrying out adaptive processing on the communication module according to the relation between the influence coefficient and an influence threshold;
the optimizing unit predicts the running state of the communication module by using the trained running model of the communication module, and carries out targeted optimization on the communication module according to the prediction result, and if the optimization result does not reach the expectation, an alarm instruction is sent out.
Based onHPLCAndHRFthe dual-mode communication device at least comprises a receiving and transmitting unit, a processing unit, a storage unit and a data interface, and is used for executing the dual-mode communication method.
HPLCAdvantages of the communication module include the following:
the communication rate is high:HPLCthe communication module adopts a high-speed carrier chip, has the characteristic of high speed, and can realize high-speed data transmission.
The communication is reliable: the module adopts a digital modulation and demodulation mode for transmission, has the advantages of strong anti-interference capability and reliable communication, and can maintain stable communication in a severe environment.
The communication distance is far:HPLCthe communication module is internally provided with a power amplifier, so that the signal transmission distance can be increased, and the remote communication can be realized.
The confidentiality is strong: the module adopts encryption technology, has extremely strong confidentiality and can ensure the safety of communication data.
In addition, in the case of the optical fiber,HPLCthe communication module also has the advantages of configurable serial port baud rate, strong availability, compatibility and support of various communication protocols, diversified communication modes and supportFECAndCRCfunction, etc.
However, the process is not limited to the above-described process,HPLCcommunication modules also have disadvantages such as high price, need for professional personnel for installation and maintenance, etc. Thus, in the selection of useHPLCWhen the communication module is used, the factors such as advantages and disadvantages, actual requirements and the like need to be comprehensively considered.
HRFThe communication module is a wireless communication module, and the advantages include the following points:
high-speed data transmission:HRFthe communication module adopts high-efficiency communication protocol and technology, can realize high-speed data transmission, and is suitable for application scenes with high requirements on quick response and real-time performance.
Long range communication capability:HRFthe communication module has stronger signal transmission capability, can realize remote communication, and is suitable for a wide geographic range or an application scene needing to cover a larger area.
High reliability and stability:HRFthe communication module adoptsThe advanced error processing technology and the stable communication protocol can effectively resist interference and noise and ensure the accuracy and the reliability of data transmission.
Flexibility:HRFthe communication module supports various communication interfaces and protocols, can be seamlessly connected and integrated with other devices, and realizes flexible communication system construction.
However, the process is not limited to the above-described process,HRFcommunication modules also have disadvantages such as high cost, high power consumption, complex installation and maintenance, and possible interference problems. Thus, in the selection of useHRFWhen the communication module is used, the factors such as advantages and disadvantages, actual requirements and the like need to be comprehensively considered.
(III) beneficial effects
The invention provides a method based onHPLCAndHRFthe dual-mode communication method, system and device have the following beneficial effects:
1. communication state coefficientThe current communication state of the communication module can be determined by evaluating and judging the communication state of the communication module and the outside; and carrying out adaptive processing on the communication module according to the judging result so as to reduce the energy consumption of the communication module and improve the data communication quality.
2. From the slaveHPLCChannel and method for transmitting dataHRFChannel selection by switching between two communication modes and according to communication state coefficientsThe switching nodes and the switching time length are determined, so that the mode switching can be more orderly and definitely performed, the communication module is adapted to different use scenes when the communication quality and the energy consumption of the communication module are relatively balanced, and the usability of the communication module is improved.
3. And judging the influence degree of the currently selected environmental condition on the communication module by performing multiple linear regression analysis, and if no influence exists, adjusting and coping with the communication module from other angles. The acquired regression equation is combined to make predictions on selected communication conditions, target communication conditions are determined, the current communication conditions of the communication module are adjusted, the adjustment process is more targeted, and the communication quality of the communication module is adjusted and improved except for switching the communication mode; the communication module and the actual use scene are more adaptive.
4. The adjusted effect is analyzed and predicted by using the constructed communication module operation model, and a plurality of optimization features are obtained by analysis on the basis of feature recognition, so that when the communication module needs to be optimized, the communication module can be more targeted, and the optimized communication module is more matched with the actual application scene when in use;
5. By constructing the optimized knowledge graph of the communication module, matching a corresponding optimization scheme from the optimized knowledge graph of the communication module according to the correspondence between the optimization features and the optimization scheme, and quickly acquiring the optimization scheme before optimizing, the time for selecting or formulating the optimization scheme can be saved, and the communication module is automatically optimized, so that the communication module has certain adaptability under different communication conditions, and the usability of the communication module is improved;
6. and carrying out trend analysis and acquiring corresponding relative strength indexes, evaluating the execution effect of the optimization scheme by using the relative strength indexes, and sending an alarm to the outside if the current optimization does not reach the expected effect, wherein at the moment, when the use state of the communication module is not good, the communication module is convenient to timely process, so that the operation risk of the communication module can be reduced.
Drawings
FIG. 1 is a flow chart of a dual mode communication method of the present invention;
FIG. 2 is a schematic diagram of a dual mode communication system according to the present invention;
fig. 3 is a schematic structural diagram of a dual-mode communication device according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention provides a method based onHPLCAndHRFcomprises the following steps:
step one, constructing a communication condition set by communication condition data of a communication module, and generating a communication condition coefficient by the communication condition setIf the acquired communication condition coefficient +.>Exceeding a condition threshold value, and sending an early warning instruction to the outside;
the first step comprises the following steps:
step 101, setting a working period, for example, taking 30 minutes or 1 hour as a working period when the communication module is in an operation state in the ammeter, and acquiring the data loss amount when the communication module exchanges data with the outside in the working periodToThe method comprises the steps of carrying out a first treatment on the surface of the When data communication is generated in a working period, if communication delay exists when data is received, the data delay amount is generatedLoThe method comprises the steps of carrying out a first treatment on the surface of the After a plurality of working cycles, a plurality of continuous data loss amountsToData delay amountLoSummarizing to generate a communication condition set of a communication module;
step 102, generating communication condition coefficients from the communication condition setThe concrete mode is as follows: amount of data lossToData delay amountLoPerforming linear normalization processing, and mapping corresponding data value to interval +. >And then according to the following mode:
wherein,nthe number of the working periods is a positive integer greater than 1,the method comprises the steps of carrying out a first treatment on the surface of the Weight coefficient:，/>and->The acquisition of the weight coefficients can be referred to by the analytic hierarchy process, said +.>Is a qualified standard value of data loss amount, +.>Is a qualified standard value of the data delay amount; what needs to be stated is: />Is the data loss amountiValues on location; />Data delay amount is atiValues on location;
presetting a condition threshold by combining historical data and management expectation of communication quality of a communication module, if the acquired communication condition coefficientWhen the condition threshold value is exceeded, the communication module is indicated to have larger load when currently running, the communication distance and the data volume are larger when the communication module is communicated with the outside, if the communication mode is not adjusted, the energy consumption generated by the communication module at present can be higher than expected, the service life of the communication module can be influenced to a certain extent, and at the moment, an early warning instruction is sent to the outside so as to facilitate the subsequent adjustment in time;
in use, the contents of steps 101 and 102 are combined:
when the communication module is in an operation state, the communication condition coefficient is generated by the communication condition set by taking data loss and data delay as reference points The current communication condition of the communication module is evaluated by the method, and multiple groups of data are integrated, so that the method has better comprehensiveness, relatively smaller deviation from the actual situation and smaller error when judging the running state of the communication module; whereas in the prior art:
when the communication module in the ammeter is used for a long time, various performances can be reduced to a certain extent, under the condition that the data is lost and delayed seriously when the communication module exchanges data with the outside, the display of the data on the ammeter can be distorted and delayed to a certain extent when the data is processed on the basis, so that certain interference and influence are brought to the use of the ammeter or similar ammeter, three-phase meter and the like.
Step two, after receiving the early warning instruction, detecting the current communication state of the communication module and constructing a communication state set, and generating a communication state coefficient by the communication state set According to the communication state coefficient->Relationship with critical threshold, for communication moduleHPLCChannel and method for transmitting dataHRFSwitching channels;
the second step comprises the following steps:
step 201, after receiving the early warning instruction, detecting the current communication state of the communication module with the outside, and constructing a communication state set, which specifically comprises the following steps:
acquiring signal stabilityQn: setting a detection period, for example, 10 minutes or 20 minutes, setting a plurality of detection nodes with equal intervals in the detection period, and detecting the signal intensity of the communication module on each detection node when the communication module is in a communication stateQThe method comprises the steps of carrying out a first treatment on the surface of the By signal strength at each nodeQCalculating signal stabilityQnThe method is as follows: according to the generation time, the signal intensities are orderly arranged along the time axis, and the following formula is adopted:
wherein,here, the number of the parts of the device, here,nfor detecting the number of nodes +.>、/>Is->The mean value, the maximum value and the minimum value of the signal intensity on each node are respectively +.>To detect nodeiSignal strength on;
referring back to the above method, the acquisition rate stability is calculated in the same mannerQu；
Continuously acquiring signal stability in a plurality of detection periodsQnRate stability QuSummarizing and constructing a communication state set of the communication module;
step 202, generating communication state coefficients from the communication state setThe concrete mode is as follows: stability to signalsQnRate stabilityQuPerforming linear normalization processing, and mapping corresponding data value to interval +.>And then according to the following mode:
wherein,is a positive integer greater than 1, +.>Which is the number of detection cycles;
weight coefficient:，/>and->The acquisition mode of the weight coefficient can refer to an analytic hierarchy process; said->Is the mean value of the signal stability, +.>Is the average value of the rate stability;
what needs to be stated is:to signal stability atiValues on location; />For rate stability atiValues on location;
in the detection of the operation state of the communication module, the signal stability is obtained by calculationQnRate stabilityQuAnd then generates a communication state coefficient from the twoThe signal stability and data transmission rate of the communication module are used as reference points, and the communication state coefficient ∈ ->The current communication state of the communication module can be determined by evaluating and judging the communication state of the communication module and the outside; according to the judging result, the communication module can be subjected to adaptive processing, so that the energy consumption of the communication module can be reduced, and the data communication quality is improved.
Step 203, from the pre-constructed communication protocol libraryHPLCChannel and method for transmitting dataHRFChannel matching corresponding communication protocol; according to the communication state coefficientThe distribution of the two communication modes is switched, and the specific mode is as follows:
setting a critical threshold for switching between two communication modes according to historical data and the expectation of communication module management;
if the acquired communication state coefficientBelow a critical threshold, thenHPLCThe channel entering the communication state, i.e. usingHPLCThe channel is communicated, if not higher than the preset value, the method causesHRFThe channel entering the communication state, i.e. usingHRFThe channel communicates; wherein the maintenance duration of the communication state and the communication state coefficient +.>The difference value between the two threshold values is positively correlated;
and after the communication mode is selected, packaging and transmitting the data to be transmitted.
In use, the contents of steps 201 to 203 are combined:
when the communication module needs to be processed, the slaveHPLCChannel and method for transmitting dataHRFChannel selection by switching between two communication modes and according to communication state coefficientsThe switching nodes and the switching time length are determined, so that the mode switching can be more ordered and clear, the mode switching cannot be unfolded due to the change of a certain parameter, and the frequency of the mode switching is further reduced; moreover, by switching the communication modes, when the communication quality and the energy consumption of the communication module are relatively balanced, the current communication module can be adapted to different use scenes, and the usability of the communication module is improved.
Step three, after the communication mode of the communication module is adjusted, constructing a regression equation by multiple regression analysis, and generating an influence coefficient by the corresponding regression coefficientAccording to influence coefficient->The relation with influencing the threshold value, make adaptive processing to the communication module;
the third step comprises the following steps:
step 301, atHPLCChannel and method for transmitting dataHRFAfter several times of switching among channels, the acquired data loss amount is obtainedToData delay amountLoAs an independent variable, by a communication state coefficientAs a dependent variable, performing multiple linear regression analysis, generating a corresponding regression equation after training and correction, and marking the regression equation as a target regression equation;
judging the communication state coefficient of the loss and delay pair of the data through the acquired target regression equationAt this time, from the target regression sideDetermining regression coefficient of the independent variable in the process, and obtaining communication condition versus communication state coefficient by the regression coefficient>Influence coefficient of->The concrete mode is as follows:
the regression coefficient is used as an influence factor to respectively obtain the data lossToData delay amountLoIs the influencing factor of (2)Is->According to the following formula:
weight coefficient:，/>the specific value of which is set by the user;
after the communication mode of the communication module is switched and used for a plurality of times, the influence degree of the currently selected environmental condition on the communication module is judged through multiple linear regression analysis, and if no influence exists, the communication module is adjusted and dealt with from other angles.
Step 302, presetting an influence threshold value by combining historical data and the expectation of communication quality management; if the coefficient of influenceBelow a preset influence threshold, it is stated that the communication conditions are relative to the communication state coefficient +.>Influence of (2)The temperature exceeds the expected temperature, at this time, the communication module is radiated, and the environment temperature where the communication module is located is reduced;
if the coefficient of influenceNot lower than a preset influence threshold, and using a target regression equation to +.>Making predictions, and after setting state expectation, obtaining communication state coefficients +>Reaching a communication condition for which a state is expected; performing correspondence adjustment on the current communication condition of the communication module, wherein the adjusted communication condition is used as a target communication condition;
in use, the contents of steps 301 and 302 are combined:
after the adjustment expectation is determined, the obtained regression equation is combined to predict the selected communication condition, and the target communication condition is determined, so that the current communication condition of the communication module can be adjusted according to the target condition, the adjustment process is more targeted, and the communication quality of the communication module is adjusted and improved except the switching of the communication mode; the communication module and the actual use scene are more adaptive.
Step four, predicting the operation state of the communication module by using the trained communication module operation model, performing targeted optimization on the communication module according to the prediction result, and sending an alarm instruction if the optimization result does not reach the expectation;
the fourth step comprises the following steps:
step 401, constructing a communication module operation model, which specifically comprises the following steps:
collecting attribute data of the communication module, including performance and specification data of the communication module, such as energy consumption and bandwidth; working environment, for example, temperature, humidity, etc. at the time of working; communication status data such as communication frequency, communication duration, etc.; after characteristic recognition is carried out on the collected data, corresponding characteristic data are obtained, and a characteristic data set is constructed after summarization;
usingBpThe neural network is used for constructing an initial model after selecting a network architecture, extracting partial data from the characteristic data set to be used as a training set and a testing set respectively, training and testing the initial model, acquiring the trained initial model, and taking the trained initial model as a communication module operation model;
step 402, performing predictive analysis on the operation of the communication module by using the trained communication module operation model and taking the target communication condition as a test condition, predicting to obtain the operation data of the communication module after an analysis period, performing feature recognition on the predicted data after setting a standard reference value and an abnormal standard, taking the recognized characteristic parameters as optimized features, and summarizing a plurality of optimized features to construct an optimized feature set;
After the communication module is correspondingly adjusted, the adjusted effect is analyzed and predicted by using the constructed communication module operation model, and a plurality of optimization features are obtained by analysis on the basis of feature recognition, so that when the communication module is required to be optimized, the communication module can be more targeted, and the optimized communication module is more matched with the actual application scene when in use;
step 403, collecting related data sets, possibly including documents, reports, news, databases, etc., by using the optimization of the communication module as a target word; cleaning the collected data, removing irrelevant information, and carrying out data standardization; for the data text which is washed, segmenting the data text data by using a natural language processing method, and extracting keywords and phrases;
using deep learning models, e.g. based onBertA kind of electronic deviceNERThe model is used for identifying key entities in the data text, such as the running environment, the communication state, the optimization characteristics, the optimization scheme and the like of the communication module; after the data are summarized, a knowledge graph data set is constructed;
determining relationships between entities in a knowledge-graph data set using a relationship extraction model in combination with a recurrent neural network model, merging identical or similar entities in the knowledge-graph Discovering implicit knowledge relationships by using a logical reasoning model or a machine learning model; usingRDFThe data model converts the data into a representation form of a knowledge graph, comprising the steps of identifying core entities, defining the relationship and the attribute among the entities, and using a unified representation mode;
constructing an initial knowledge graph, including building entity nodes in the graph and relation edges between the entity nodes, selecting a graph database or a graph storage system, and loading data into the graph database or the graph storage system; based on verification and evaluation, carrying out iteration and optimization adjustment on an initial knowledge graph, expanding the range and depth of the graph, and increasing the richness and accuracy of data;
acquiring an initial knowledge graph after training and optimization, and taking the initial knowledge graph as an optimized knowledge graph of a communication module;
when the communication module is required to be optimized, a trained matching model is used, a corresponding optimization scheme is matched from an optimization knowledge graph of the communication module according to the correspondence between the optimization features and the optimization scheme, and the communication module executes the optimization scheme;
step 404, setting an observation period, for example, making the observation period equal to the detection period, and after a plurality of observation periods, continuously acquiring a plurality of communication state coefficients Orderly arranged along a time axis to acquire a communication state data column; trend analysis is carried out on the communication state data sequence, corresponding relative strength indexes are obtained, and if the relative strength indexes do not fall into a preset range, an alarm instruction is sent out;
the relative strength index is an index for describing trend change in time series data, and is used for quantifying the change speed and direction of the trend, and the relative strength index can help us to know the trend characteristics of the data, including the increase speed, the change amplitude and the direction of the trend.
Trend verification is a statistical method for determining whether there is a significant trend change in time series data. Trend verification can help us know whether the data shows a steady trend, as well as the direction and significance of the trend.
In use, the contents of steps 401 to 404 are combined:
when the operation of the communication module is required to be optimized, a corresponding optimization scheme is matched from the optimization knowledge graph of the communication module according to the correspondence between the optimization features and the optimization scheme by constructing the optimization knowledge graph of the communication module, the time for selecting or formulating the optimization scheme can be saved by quickly acquiring the optimization scheme before optimizing, and the communication module has certain adaptability under different communication conditions by automatically optimizing the communication module, so that the usability of the communication module is improved;
Further, through trend analysis and corresponding relative strength index acquisition, the execution effect of the optimization scheme is evaluated according to the relative strength index, if the current optimization does not reach the expected effect, an alarm is sent to the outside, and at the moment, when the use state of the communication module is not good, timely processing is facilitated, so that the operation risk of the communication module can be reduced.
It should be noted that: the analytic hierarchy process is a qualitative and quantitative combined analytic method, can decompose a complex problem into a plurality of layers, can help a decision maker to make a decision on the complex problem by comparing the importance of each layer factor, and determines a final decision scheme, wherein the analytic hierarchy process can be used for determining the weight coefficients of the indexes in the process; the steps of the analytic hierarchy process are as follows:
explicit problem: firstly, determining a decision problem, and determining a decision target and an alternative scheme;
establishing a hierarchical structure model: decomposing the problem into different layers according to the nature of the problem and a decision target, wherein the different layers generally comprise a target layer, a criterion layer and a scheme layer; the target layer is the overall target of the decision problem, the criterion layer is the criterion for evaluating the alternatives, and the scheme layer is the alternatives;
Constructing a judgment matrix: the judgment matrix is constructed by comparing the importance of the elements in the same layer with respect to one element in the upper layer. Judging that the elements in the matrix represent the ratio of the relative importance of the two elements;
hierarchical single ordering: and according to the judgment matrix, calculating the relative importance ranking weight of the elements in the same layer relative to a certain element in the upper layer. This process is called hierarchical single ordering;
consistency test: and checking consistency of the judging matrix, namely checking whether the judging matrix meets consistency conditions. If the consistency condition is met, the hierarchical single sequencing result is considered to be reasonable;
hierarchical total ordering: calculating the composite weight of each layer of elements on a system target, and carrying out total sequencing to determine the total sequencing weight of each element at the bottommost layer in the hierarchical structure diagram;
through an analytic hierarchy process, a decision maker can decompose a complex decision problem into different layers and make decisions based on qualitative and quantitative analysis; the method can improve the accuracy and the effectiveness of decision making, and is particularly suitable for complex problems which are difficult to solve by a quantitative method.
Referring to fig. 2, the present invention provides a method based onHPLCAndHRFa dual mode communication system of (1), comprising:
The early warning unit constructs a communication condition set by the communication condition data of the communication module, further generates a communication condition coefficient by the communication condition set, and sends an early warning instruction to the outside if the acquired communication condition coefficient exceeds a condition threshold value;
the switching unit is used for detecting the current communication state of the communication module and constructing a communication state set after receiving the early warning instruction, generating a communication state coefficient by the communication state set, and carrying out the relation between the communication state coefficient and a critical threshold value on the communication moduleHPLCChannel and method for transmitting dataHRFSwitching channels;
the analysis unit is used for constructing a regression equation after adjusting the communication mode of the communication module, generating an influence coefficient by the corresponding regression coefficient, and carrying out adaptive processing on the communication module according to the relation between the influence coefficient and an influence threshold;
the optimizing unit predicts the running state of the communication module by using the trained running model of the communication module, and carries out targeted optimization on the communication module according to the prediction result, and if the optimization result does not reach the expectation, an alarm instruction is sent out.
Referring to fig. 3, the present invention provides a method based onHPLCAndHRFat least a transceiver unit, a processing unit, a memory unit, a data interface, etc.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in accordance with the embodiments of the present application are all or partially produced. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more sets of available media. The usable medium may be magnetic medium (e.g., floppy disk, hard disk, magnetic tape), optical medium (e.g., DVD) Or a semiconductor medium. The semiconductor medium may be a solid state disk.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is merely a channel underwater topography change analysis system and method logic function division, and other divisions may be implemented in practice, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application is essentially or partly contributing to the prior art or part of the technical solutionMay be embodied in the form of a software product stored on a storage medium comprising instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of a method as described in various embodiments of the present application. And the aforementioned storage medium includes: UDisc, mobile hard disc and ROMread-onlymemory，ROM) Random access memoryrandomaccessmemory，RAM) Various media such as magnetic or optical disks that can store program code.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered by the scope of the present application.
Claims (6)
1. A dual mode communication method based on HPLC and HRF, characterized in that: comprising the steps of (a) a step of,
constructing a communication condition set by the communication condition data of the communication module, generating a communication condition coefficient Ts (o, o) by the communication condition set, and sending an early warning instruction to the outside if the acquired communication condition coefficient Ts (o, o) exceeds a condition threshold value;
After receiving the early warning instruction, detecting the current communication state of the communication module, constructing a communication state set, generating a communication state coefficient Qo (u, n) by the communication state set, and switching an HPLC channel and an HRF channel in the communication module according to the relation between the communication state coefficient Qo (u, n) and a critical threshold; the communication condition coefficients Ts (o, o) are generated as follows: the data loss To and the data delay Lo are subjected To linear normalization processing, corresponding data values are mapped into intervals [0,1], and then the following mode is adopted:
wherein n is the number of working periods, is a positive integer greater than 1, i=1, 2, …, n; weight coefficient: ζ is greater than or equal to 0 and less than or equal to 1, χ is greater than or equal to 0 and less than or equal to 1, and ζ+χ=1, whereinIs a qualified standard value of data loss amount, +.>Is a qualified standard value of the data delay amount;
after the communication mode of the communication module is adjusted, a regression equation is constructed by multiple regression analysis, and an influence coefficient is generated by the corresponding regression coefficientAccording to influence coefficient->The relation with influencing the threshold value, make adaptive processing to the communication module;
predicting the running state of the communication module by using the trained communication module running model, performing targeted optimization on the communication module according to the prediction result, and sending an alarm instruction if the optimization result does not reach the expectation;
In a working period, acquiring the data loss To when the communication module exchanges data with the outside; when data communication is generated in a working period, if communication delay exists when data is received, generating a data delay amount Lo; summarizing a plurality of continuous data loss To and data delay Lo To generate a communication condition set of a communication module;
continuously acquiring signal stability Qn and rate stability Qu in a plurality of detection periods, and constructing a communication state set of a communication module after summarizing; the method for acquiring the communication state coefficient Qo (u, n) is as follows: the signal stability Qn and the rate stability Qu are subjected to linear normalization processing, corresponding data values are mapped into intervals [0,1], and then the following mode is adopted:
wherein m is a positive integer greater than 1, i=1, 2, …, m, which is the number of detection cycles; weight coefficient: f is 0 to or less 1 ≤1，0≤F 2 F is less than or equal to 1 2 +F 1 =1, the Qn avg As an average value of signal stability, qu avg Is the average value of the rate stability;
matching corresponding communication protocols for the HPLC channel and the HRF channel from a pre-constructed communication protocol library; according to the distribution of the communication state coefficients Qo (u, n), the two communication modes are switched, and the specific modes are as follows:
If the acquired communication state coefficient Qo (u, n) is lower than a critical threshold, enabling the HPLC channel to enter a communication state, and if not, enabling the HRF channel to enter the communication state; wherein, the maintaining time of the communication state and the difference value between the communication state coefficient Qo (u, n) and the critical threshold value are positively correlated; after the communication mode is selected, packaging and transmitting data to be transmitted;
after switching between an HPLC channel and an HRF channel for a plurality of times, taking the acquired data loss To and the data delay Lo as independent variables, taking a communication state coefficient Qo (u, n) as a dependent variable, and performing multiple linear regression analysis To generate a target regression equation; determining regression coefficients of the independent variables from the target regression equation, and acquiring influence coefficients of communication conditions on communication state coefficients Qo (u, n) from the regression coefficientsThe concrete mode is as follows: the regression coefficient is used as an influence factor To respectively obtain the data loss To and the data loss numberInfluence factor psi according to delay Lo T Psi (phi) L According to the following formula:
weight coefficient:the specific value of which is set by the user.
2. A dual mode communication method based on HPLC and HRF according to claim 1, wherein:
if the coefficient of influenceThe communication module is cooled below a preset influence threshold value, and if the influence coefficient is + - >Not lower than the preset influence threshold, predicting the communication state coefficient Qo (u, n) by using a target regression equation, and obtaining the communication condition for enabling the communication state coefficient Qo (u, n) to reach the state expectation; and correspondingly adjusting the current communication condition of the communication module, wherein the adjusted communication condition is used as a target communication condition.
3. A dual mode communication method based on HPLC and HRF according to claim 2, wherein:
after the initial model is trained and tested by using a Bp neural network, the trained initial model is used as a communication module operation model, target communication conditions are used as test conditions, the trained communication module operation model is used for carrying out predictive analysis on the operation of the communication module, the operation data of the communication module are obtained through prediction, feature recognition is carried out on the prediction data, the obtained feature parameters are recognized as optimization features, a plurality of optimization features are summarized, and an optimization feature set is constructed.
4. A dual mode communication method based on HPLC and HRF according to claim 3, wherein:
taking optimization of the communication module as a target word, and constructing an optimized knowledge graph of the communication module; according to the correspondence between the optimization features and the optimization schemes, matching a corresponding optimization scheme from the optimization knowledge graph of the communication module, and executing the optimization scheme by the communication module;
After a plurality of observation periods, orderly arranging a plurality of continuously acquired communication state coefficients Qo (u, n) along a time axis to acquire a communication state data sequence; and carrying out trend analysis on the communication state data sequence, acquiring corresponding relative strength indexes, and sending out an alarm instruction if the relative strength indexes do not fall into a preset range.
5. A dual mode communication system based on HPLC and HRF, to which the method of any one of claims 1-4 is applied, characterized in that: comprising the following steps:
the early warning unit constructs a communication condition set by the communication condition data of the communication module, further generates a communication condition coefficient by the communication condition set, and sends an early warning instruction to the outside if the acquired communication condition coefficient exceeds a condition threshold value;
the switching unit is used for detecting the current communication state of the communication module and constructing a communication state set after receiving the early warning instruction, generating a communication state coefficient by the communication state set, and switching an HPLC channel and an HRF channel in the communication module according to the relation between the communication state coefficient and a critical threshold;
the analysis unit is used for constructing a regression equation after adjusting the communication mode of the communication module, generating an influence coefficient by the corresponding regression coefficient, and carrying out adaptive processing on the communication module according to the relation between the influence coefficient and an influence threshold;
The optimizing unit predicts the running state of the communication module by using the trained running model of the communication module, and carries out targeted optimization on the communication module according to the prediction result, and if the optimization result does not reach the expectation, an alarm instruction is sent out.
6. A dual mode HPLC and HRF based communication apparatus for performing the method of any one of claims 1-4, wherein: the device at least comprises a receiving and transmitting unit, a processing unit, a storage unit and a data interface.
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