CN115098323A - Signal access method based on big data - Google Patents
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Abstract
The invention discloses a big data-based signal access method, which comprises the steps of obtaining signal request data, and processing the signal request data to obtain signal request processing data; acquiring signal operation data, and processing the signal operation data to obtain signal operation processing data; calculating the signal request processing data to obtain a signal request value, and performing matching analysis on the signal request value and a preset standard signal request range to obtain a signal request analysis set; calculating the signal operation processing data to obtain a credit value, and performing matching analysis on the credit value and a preset credit threshold value to obtain a credit analysis set; the credit request analysis set and the credit operation analysis set are matched in a simultaneous mode to obtain a matching result, and the signal request data and the signal port are accessed according to the matching result, so that the defect that the effect of signal access is poor due to the fact that analysis and dynamic matching cannot be conducted according to the signal request data and the access operation data is overcome.
Description
Technical Field
The invention relates to the technical field of big data, in particular to a big data-based signal access method.
Background
A signal is a physical quantity representing a message, e.g. an electrical signal may represent different messages by variations in amplitude, frequency, phase. Such electrical signals are classified into analog signals and digital signals. The signal is a vehicle for carrying the message and is a carrier of the message. In a broad sense it encompasses optical, acoustic, electrical and the like. The signals are distinguished according to actual purposes, and comprise television signals, broadcast signals, radar signals, communication signals and the like; the signals are distinguished according to the time characteristics, and then a deterministic signal, a random signal and the like exist;
the classification method of the signals is various, and the signals can be divided into deterministic signals and non-deterministic signals, continuous signals and discrete signals, energy signals and power signals, time domain signals and frequency domain signals, time limit signals and frequency limit signals, real signals and complex signals and the like according to mathematical relations, value characteristics, energy power, processing analysis, time function characteristics, real value and the like;
publication number CN111966010A discloses a signal access module, comprising: the communication interface is used for receiving communication signals, the transformer is used for coupling the signals, and at least two data communication modules are used for identifying the signal type of the communication signals and communicating with the communication interface according to the signal type; each signal coupling end of the transformer is connected with the signal coupling end of each data communication module, and the input end of the transformer is connected with the communication interface. Wherein each data communication module identifies communication signals of one signal type, and the signal types identified between the data communication modules are different. The embodiment of the invention also discloses a control method of the signal access module and signal access equipment, which can effectively solve the problem that the G.fast signal and the VDSL signal in the prior art can not be compatible.
But has the defect that the signal access effect is poor because the analysis and dynamic matching can not be carried out according to the signal request data and the access operation data.
Disclosure of Invention
The invention aims to provide a big data-based signal access method, and mainly aims to solve the technical problem of poor signal access effect caused by the fact that analysis and dynamic matching cannot be carried out according to signal request data and access operation data.
The purpose of the invention can be realized by the following technical method: a big data based signal access method comprises the following working steps:
the method comprises the following steps: acquiring signal request data, wherein the signal request data comprises a signal request type, a signal request sender, a signal request occupation and a signal request frequency, and processing the signal request data to obtain signal request processing data;
step two: acquiring signal operation data, wherein the signal operation data comprises a port operation type, a port operation time and a port operation temperature, and processing the signal operation data to obtain signal operation processing data;
step three: calculating the signal request processing data to obtain a signal request value, and performing matching analysis on the signal request value and a preset standard signal request range to obtain a signal request analysis set;
step four: calculating the signal operation processing data to obtain a credit value, and performing matching analysis on the credit value and a preset credit threshold value to obtain a credit analysis set;
step five: and performing simultaneous matching on the credit request analysis set and the credit operation analysis set to obtain a matching result, and accessing the signal request data and the signal port according to the matching result.
Further, the specific step of performing processing operation on the signal request data to obtain the signal request processing data includes:
s21: acquiring a signal request type, a signal request sender, a signal request occupation and a signal request frequency in signal request data;
s22: marking the signal request type as XQLi, i ═ 1,2.. n; setting different signal types to correspond to different signal preset values, matching the signal request type with all the signal types to obtain the corresponding signal preset value, and marking the signal preset value as XYZ, i is 1,2.. n;
s23: marking a signal request sender as XQFi, i ═ 1,2.. n; setting different senders to correspond to different sending weights, matching the signal request sender with all the senders to obtain the corresponding sending weights, and marking the sending weights as FQZi, i is 1,2.. n;
s24: marking the signal request occupancy as XQZi, i ═ 1,2.. n; marking the signal request frequency as XQPi, i ═ 1,2.. n; setting different signal frequencies to correspond to different frequency preset values, matching the signal request frequency with all the signal frequencies to obtain corresponding frequency preset values, and marking the corresponding frequency preset values as XPYi, wherein i is 1,2.. n;
s25: and combining the marked signal request type, the signal preset value, the signal request sender, the sending weight, the signal request occupation, the signal request frequency and the frequency preset value to obtain signal request processing data.
Further, the specific steps of performing processing operation on the signal operation data to obtain signal operation processing data include:
s31: acquiring a port operation type, a port operation time and a port operation temperature in the signal operation data;
s32: marking a port operation type as DYLi, i is 1,2.. n; setting different port types to correspond to different port preset values, matching the port operation type with all the port types to obtain corresponding port preset values, and marking the corresponding port preset values as DYSI, wherein i is 1,2.. n;
s33: marking the total operation time length in the port operation time as YZSi, wherein i is 1,2.. n; marking the total number of times of operation in the port operation time as YZCi, i is 1,2.. n;
s34: marking the port operating temperature as DYwi, i ═ 1,2.. n; acquiring the ambient temperature of the port operation, and marking the ambient temperature as HWi, i ═ 1,2.. n;
s35: and combining the marked port operation type, the port preset value, the total operation time, the total operation times, the port operation temperature and the environment temperature to obtain signal operation processing data.
Further, the signal request processing data is calculated to obtain a signal request value, the signal request value is subjected to matching analysis with a preset standard signal request range to obtain a signal request analysis set, and the specific steps include:
s41: receiving a signal request type XQLi, a signal preset value XYZi, a signal request sender XQFi, a sending weight FQZi, a signal request occupation XQZi, a signal request frequency XQPi and a frequency preset value XPYi marked in signal request processing data, and carrying out normalization processing and value taking on the signal preset value, the sending weight, the signal request occupation and the frequency preset value;
s42: calculating to obtain a credit value by using a formula; the formula is
Wherein, XQ i Expressed as signal request values, a1, a2, a3 and a4 are expressed as preset scaling factors, and mu is expressed as a preset signal request correction factor;
s43: matching the signal request value with a preset standard signal request range, acquiring a signal request sub-range containing the signal request value in the standard signal request range and a plurality of associated signal ports, and performing descending order arrangement on the signal ports according to the signal request sub-value in the signal request sub-range to obtain a port ordering set;
s44: and classifying and combining the information request value and the port sequencing set to obtain an information request analysis set.
Further, the signal operation processing data is calculated to obtain a credit value, the credit value is matched and analyzed with a preset credit threshold value to obtain a credit analysis set, and the specific steps comprise:
s51: acquiring a port operation type DYLi, a port preset value DYSi, a total operation time YZSi, a total operation frequency YZCi, a port operation temperature DYWi and an environment temperature HWi which are marked in signal operation processing data;
s52: calculating by using a formula to obtain a credit value; the formula is
Wherein XY i Expressed as a traffic value, b1, b2, b3 and b4 are expressed as preset proportionality coefficients, k is expressed as the total number of signal ports, DYSI0 is expressed as an accumulated value of the preset values of the ports, and WCi is expressed as a preset standard temperature difference value;
s53: matching the credit value with a preset standard credit threshold, and if the credit value is not greater than the standard credit threshold, judging that a signal port corresponding to the credit value is not in operation and can be accessed and generating a first credit signal; marking the signal port as an effective port according to the first signal transmission signal; if the credit value is greater than the standard credit threshold value, judging that the signal port corresponding to the credit value is not accessible during operation and generating a second credit signal; marking the signal port as an invalid port according to the second signal;
s54: and combining the first signal and the second signal and the corresponding valid port and invalid port to obtain a signal analysis set.
Further, the letter request analysis set and the letter operation analysis set are matched in a simultaneous mode to obtain a matching result, and the specific steps include:
s61: receiving a message request analysis set and a message and motion analysis set and carrying out simultaneous analysis;
s62: matching a port sorting set in the message request analysis set with a plurality of effective ports in the message operation analysis set, and setting the port sorting set as a selected port if the port sorting set has a signal port which is the same as the effective port; if the port sorting set does not have the signal port same as the effective port, judging that the effective port is not matched with the signal port in the port sorting set and generating a first matching signal;
s63: matching a port sequencing set in a message request analysis set with a plurality of effective ports in a message operation analysis set according to a first matching signal, and setting the port sequencing set as a port to be selected if a signal port identical to an invalid port exists in the port sequencing set; if the signal port which is the same as the invalid port does not exist in the port sequencing set, judging that the invalid port is not matched with the signal port in the port sequencing set and generating a second matching signal; generating a re-access prompt according to the second matching signal;
s64: acquiring the state of a port to be selected, and if the state is an operating state, generating a waiting signal to enable signal request data to wait and access; if the state is a fault state, a return signal is generated so that the signal request data can be applied for access again.
The invention has the beneficial effects that:
in various aspects disclosed by the invention, signal request data is obtained, the signal request data comprises a signal request type, a signal request sender, a signal request occupation and a signal request frequency, and the signal request data is processed to obtain signal request processing data; by acquiring and processing the signal request data, each data item in the signal request data is convenient to calculate and establish a relationship, so that the efficiency and the accuracy of analyzing the signal request data are improved;
acquiring signal operation data, wherein the signal operation data comprises a port operation type, a port operation time and a port operation temperature, and processing the signal operation data to obtain signal operation processing data; by acquiring the signal operation data and performing processing operation, the accuracy of the processing and analyzing operation of the signal operation data can be improved, and effective data support can be further provided for subsequent signal matching and access;
calculating the signal request processing data to obtain a signal request value, and performing matching analysis on the signal request value and a preset standard signal request range to obtain a signal request analysis set; by calculating and analyzing the signal request processing data, the data items of the signal request processing data are linked, so that the signal request processing data can be integrally analyzed;
calculating the signal operation processing data to obtain a credit value, and performing matching analysis on the credit value and a preset credit threshold value to obtain a credit analysis set; by calculating and matching the signal operation processing data, the relation among all data items of the signal operation processing data can be established, the overall situation of the operation processing data is conveniently monitored, and the signals to be accessed can be efficiently and accurately matched;
performing simultaneous matching on the credit request analysis set and the credit operation analysis set to obtain a matching result, and accessing the signal request data and the signal port according to the matching result; the method can achieve the purpose of improving the signal access effect by analyzing and dynamically matching according to the signal request data and the access operation data, and overcome the defects of poor matching efficiency and accuracy caused by single factors of access signal analysis in the existing scheme.
Drawings
The invention will be further described with reference to the accompanying drawings.
Fig. 1 is a schematic flowchart of a big data based signal access method according to the present invention.
Detailed Description
The technical method in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example one
Referring to fig. 1, the present invention is a big data based signal access method, which includes the following steps:
the method comprises the following steps: acquiring signal request data, wherein the signal request data comprises a signal request type, a signal request sender, a signal request occupation and a signal request frequency, and processing the signal request data to obtain signal request processing data; the method comprises the following specific steps:
acquiring a signal request type, a signal request sender, a signal request occupation and a signal request frequency in signal request data;
marking the signal request type as XQLi, i ═ 1,2.. n; setting different signal types to correspond to different signal preset values, matching the signal request type with all the signal types to obtain the corresponding signal preset values, and marking the corresponding signal preset values as XYZi, wherein i is 1,2.. n;
marking a signal request sender as XQFi, i ═ 1,2.. n; setting different senders to correspond to different sending weights, matching the signal request sender with all the senders to obtain the corresponding sending weights, and marking the sending weights as FQZi, i is 1,2.. n;
marking the signal request occupancy as XQZi, i ═ 1,2.. n; marking the signal request frequency as XQPi, i ═ 1,2.. n; setting different signal frequencies to correspond to different frequency preset values, matching the signal request frequency with all the signal frequencies to obtain corresponding frequency preset values, and marking the corresponding frequency preset values as XPYi, wherein i is 1,2.. n;
combining the marked signal request type, the signal preset value, the signal request sender, the sending weight, the signal request occupation, the signal request frequency and the frequency preset value to obtain signal request processing data;
step two: acquiring signal operation data, wherein the signal operation data comprises a port operation type, a port operation time and a port operation temperature, and processing the signal operation data to obtain signal operation processing data; the method comprises the following specific steps:
acquiring a port operation type, a port operation time and a port operation temperature in the signal operation data;
marking a port operation type as DYLi, i is 1,2.. n; setting different port types to correspond to different port preset values, matching the port operation type with all the port types to obtain the corresponding port preset values, and marking the port preset values as DYSI, wherein i is 1,2.. n;
marking the total running time in the running time of the port as YZSi, i is 1,2.. n; marking the total number of times of operation in the port operation time as YZCi, i is 1,2.. n;
marking the port operating temperature as DYwi, i-1, 2.. n; acquiring the ambient temperature of the port operation, and marking the ambient temperature as HWi, i ═ 1,2.. n;
combining the marked port operation type, the port preset value, the total operation time, the total operation times, the port operation temperature and the environment temperature to obtain signal operation processing data;
step three: calculating the signal request processing data to obtain a signal request value, and performing matching analysis on the signal request value and a preset standard signal request range to obtain a signal request analysis set; the method comprises the following specific steps:
receiving a signal request type XQLi, a signal preset value XYZi, a signal request sender XQFi, a sending weight FQZi, a signal request occupation XQZi, a signal request frequency XQPi and a frequency preset value XPYi marked in signal request processing data, and carrying out normalization processing and value taking on the signal preset value, the sending weight, the signal request occupation and the frequency preset value;
calculating to obtain a credit value by using a formula; the formula is
Wherein, XQ i Expressed as signal request values, a1, a2, a3 and a4 are expressed as preset scaling factors, and μ is expressed as a preset signal request correction factor;
matching the signal request value with a preset standard signal request range, acquiring a signal request sub-range containing the signal request value in the standard signal request range and a plurality of associated signal ports, and performing descending order arrangement on the signal ports according to the signal request sub-value in the signal request sub-range to obtain a port ordering set;
classifying and combining the credit request value and the port sequencing set to obtain a credit request analysis set;
step four: calculating the signal operation processing data to obtain a credit value, and performing matching analysis on the credit value and a preset credit threshold value to obtain a credit analysis set; the method comprises the following specific steps:
acquiring a port operation type DYLi, a port preset value DYSi, a total operation time YZSi, a total operation frequency YZCi, a port operation temperature DYWi and an environment temperature HWi which are marked in signal operation processing data;
calculating to obtain a credit value by using a formula; the formula is
Wherein XY i Expressed as a traffic value, b1, b2, b3 and b4 are expressed as preset proportionality coefficients, k is expressed as the total number of signal ports, DYSI0 is expressed as an accumulated value of port preset values, and WCi is expressed as a preset standard temperature difference value;
matching the credit value with a preset standard credit threshold, and if the credit value is not greater than the standard credit threshold, judging that a signal port corresponding to the credit value is not in operation and can be accessed and generating a first credit signal; marking the signal port as an effective port according to the first signal transmission signal; if the credit value is greater than the standard credit threshold value, judging that the signal port corresponding to the credit value is not accessible during operation and generating a second credit signal; marking the signal port as an invalid port according to the second signal;
combining the first signal and the second signal and the corresponding effective port and invalid port to obtain a signal analysis set;
step five: performing simultaneous matching on the credit request analysis set and the credit operation analysis set to obtain a matching result, and accessing the signal request data and the signal port according to the matching result, wherein the specific steps comprise:
receiving a request analysis set and a credit and transit analysis set and carrying out simultaneous analysis;
matching a port sequencing set in the signal request analysis set with a plurality of effective ports in the signal operation analysis set, and setting the port sequencing set as a selected port if the port sequencing set has signal ports which are the same as the effective ports; if the port sorting set does not have the signal port same as the effective port, judging that the effective port is not matched with the signal port in the port sorting set and generating a first matching signal; the first matching signal indicates that the signal access port of the signal request data request is not matched with the accessible port in the idle state and signal access cannot be carried out;
matching a port sequencing set in a message request analysis set with a plurality of effective ports in a message operation analysis set according to a first matching signal, and setting the port sequencing set as a port to be selected if a signal port identical to an invalid port exists in the port sequencing set; if the signal port which is the same as the invalid port does not exist in the port sequencing set, judging that the invalid port is not matched with the signal port in the port sequencing set and generating a second matching signal; generating a re-access prompt according to the second matching signal; the second matching signal indicates that the signal access port of the signal request data request is in an abnormal and non-working state, so that the signal access cannot be carried out, and the port to be selected indicates that the port is matched with the signal access port of the signal request data request but is in a working state;
acquiring the state of a port to be selected, and if the state is an operating state, generating a waiting signal to enable signal request data to wait and access; if the state is a fault state, generating a return signal to enable the signal request data to apply for access again;
the working principle of the embodiment of the invention is as follows: in the embodiment of the invention, signal request data is obtained, the signal request data comprises a signal request type, a signal request sender, a signal request occupation and a signal request frequency, and the signal request data is processed to obtain signal request processing data; by acquiring and processing the signal request data, each data item in the signal request data is convenient to calculate and establish a relationship, so that the efficiency and the accuracy of analyzing the signal request data are improved;
acquiring signal operation data, wherein the signal operation data comprises a port operation type, a port operation time and a port operation temperature, and processing the signal operation data to obtain signal operation processing data; by acquiring the signal operation data and performing processing operation, the accuracy of the processing and analyzing operation of the signal operation data can be improved, and effective data support can be provided for subsequent signal matching and access;
calculating the signal request processing data by using a formula
Calculating to obtain a credit value; matching the signal request value with a preset standard signal request range, acquiring a signal request sub-range containing the signal request value in the standard signal request range and a plurality of associated signal ports, and performing descending order arrangement on the signal ports according to the signal request sub-value in the signal request sub-range to obtain a port ordering set; classifying and combining the credit request value and the port sequencing set to obtain a credit request analysis set; by calculating and analyzing the signal request processing data, the data items of the signal request processing data are linked, so that the signal request processing data can be integrally analyzed;
counting signal operation processing dataCalculation, utilization of formula
Calculating to obtain a credit value; matching the credit value with a preset standard credit threshold, and if the credit value is not greater than the standard credit threshold, judging that a signal port corresponding to the credit value is not in operation and can be accessed and generating a first credit signal; marking the signal port as an active port according to a first signal; if the credit value is greater than the standard credit threshold value, judging that the signal port corresponding to the credit value is not accessible during operation and generating a second credit signal; marking the signal port as an invalid port according to the second signal; combining the first signal and the second signal and the corresponding effective port and invalid port to obtain a signal analysis set; by calculating and matching the signal operation processing data, the relation among all data items of the signal operation processing data can be established, the overall situation of the operation processing data is conveniently monitored, and the signals to be accessed can be efficiently and accurately matched;
performing simultaneous matching on the credit request analysis set and the credit operation analysis set to obtain a matching result, and accessing the signal request data and the signal port according to the matching result; matching a port sequencing set in the signal request analysis set with a plurality of effective ports in the signal operation analysis set, and setting the port sequencing set as a selected port if the port sequencing set has signal ports which are the same as the effective ports; if the port sorting set does not have the signal port same as the effective port, judging that the effective port is not matched with the signal port in the port sorting set and generating a first matching signal; matching a port sequencing set in a message request analysis set with a plurality of effective ports in a message operation analysis set according to a first matching signal, and setting the port sequencing set as a port to be selected if a signal port identical to an invalid port exists in the port sequencing set; if the signal port which is the same as the invalid port does not exist in the port sequencing set, judging that the invalid port is not matched with the signal port in the port sequencing set and generating a second matching signal; generating a re-access prompt according to the second matching signal; acquiring the state of a port to be selected, and if the state is an operating state, generating a waiting signal to enable signal request data to wait and access; if the state is a fault state, generating a return signal to enable the signal request data to apply for access again; the method can achieve the purpose of improving the signal access effect by analyzing and dynamically matching according to the signal request data and the access operation data, and overcome the defects of poor matching efficiency and accuracy caused by single factors of access signal analysis in the existing scheme.
In the embodiments provided by the present invention, it should be understood that the disclosed apparatus, device and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and the parts displayed as modules may or may not be physical units, that is, may be located in one place, or may also be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the method of the embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. Several units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above examples are only for illustrating the technical method of the present invention and not for limiting, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made to the technical method of the present invention without departing from the spirit and scope of the technical method of the present invention.
Claims (6)
1. A big data-based signal access method is characterized in that the working steps of the signal access method comprise:
the method comprises the following steps: acquiring signal request data, wherein the signal request data comprises a signal request type, a signal request sender, a signal request occupation and a signal request frequency, and processing the signal request data to obtain signal request processing data;
step two: acquiring signal operation data, wherein the signal operation data comprises a port operation type, a port operation time and a port operation temperature, and processing the signal operation data to obtain signal operation processing data;
step three: calculating the signal request processing data to obtain a signal request value, and performing matching analysis on the signal request value and a preset standard signal request range to obtain a signal request analysis set;
step four: calculating the signal operation processing data to obtain a credit value, and performing matching analysis on the credit value and a preset credit threshold value to obtain a credit analysis set;
step five: and performing simultaneous matching on the credit request analysis set and the credit operation analysis set to obtain a matching result, and accessing the signal request data and the signal port according to the matching result.
2. The big-data-based signal access method according to claim 1, wherein the step of performing processing operation on the signal request data to obtain the signal request processing data comprises:
s21: acquiring a signal request type, a signal request sender, a signal request occupation and a signal request frequency in signal request data;
s22: marking the signal request type as XQLi, i ═ 1,2.. n; setting different signal types to correspond to different signal preset values, matching the signal request type with all the signal types to obtain the corresponding signal preset values, and marking the corresponding signal preset values as XYZi, wherein i is 1,2.. n;
s23: marking a signal request sender as XQFi, i ═ 1,2.. n; setting different senders to correspond to different sending weights, matching the signal request sender with all the senders to obtain the corresponding sending weights, and marking the sending weights as FQZi, i is 1,2.. n;
s24: marking the signal request occupancy as XQZi, i ═ 1,2.. n; marking the signal request frequency as XQPi, i ═ 1,2.. n; setting different signal frequencies to correspond to different frequency preset values, matching the signal request frequency with all the signal frequencies to obtain corresponding frequency preset values, and marking the corresponding frequency preset values as XPYi, wherein i is 1,2.. n;
s25: and combining the marked signal request type, the signal preset value, the signal request sender, the sending weight, the signal request occupation, the signal request frequency and the frequency preset value to obtain signal request processing data.
3. The big-data-based signal access method according to claim 2, wherein the specific step of performing processing operation on the signal operation data to obtain the signal operation processing data comprises:
s31: acquiring a port operation type, a port operation time and a port operation temperature in the signal operation data;
s32: marking a port operation type as DYLi, i is 1,2.. n; setting different port types to correspond to different port preset values, matching the port operation type with all the port types to obtain the corresponding port preset values, and marking the port preset values as DYSI, wherein i is 1,2.. n;
s33: marking the total running time in the running time of the port as YZSi, i is 1,2.. n; marking the total number of operation times in the port operation time as YZCi, wherein i is 1,2.. n;
s34: marking the port operating temperature as DYwi, i ═ 1,2.. n; acquiring the ambient temperature of the port operation, and marking the ambient temperature as HWi, i ═ 1,2.. n;
s35: and combining the marked port operation type, the port preset value, the total operation time, the total operation times, the port operation temperature and the environment temperature to obtain signal operation processing data.
4. The big data based signal access method according to claim 3, wherein the signal request processing data is calculated to obtain a request value, the request value is subjected to matching analysis with a preset standard request range to obtain a request analysis set, and the specific steps include:
s41: receiving a signal request type XQLi, a signal preset value XYZi, a signal request sender XQFi, a sending weight FQZi, a signal request occupation XQZi, a signal request frequency XQPi and a frequency preset value XPYi marked in signal request processing data, and carrying out normalization processing and value taking on the signal preset value, the sending weight, the signal request occupation and the frequency preset value;
s42: calculating by using a formula to obtain a message value; the formula is
Wherein, XQ i Expressed as signal request values, a1, a2, a3 and a4 are expressed as preset scaling factors, and μ is expressed as a preset signal request correction factor;
s43: matching the signal request value with a preset standard signal request range, acquiring a signal request sub-range containing the signal request value in the standard signal request range and a plurality of signal ports related to the signal request sub-range, and performing descending order on the signal ports according to the signal request sub-value in the signal request sub-range to obtain a port ordering set;
s44: and classifying and combining the information request value and the port sequencing set to obtain an information request analysis set.
5. The big data-based signal access method according to claim 4, wherein the signal operation processing data is calculated to obtain a credit value, the credit value is subjected to matching analysis with a preset credit threshold value to obtain a credit analysis set, and the specific steps include:
s51: acquiring a port operation type DYLi, a port preset value DYSI, a total operation time length YZSi, a total operation times YZCi, a port operation temperature DYwi and an environment temperature HWi which are marked in the signal operation processing data;
s52: calculating by using a formula to obtain a credit value; the formula is
Wherein XY i Expressed as a traffic value, b1, b2, b3 and b4 are expressed as preset proportionality coefficients, k is expressed as the total number of signal ports, DYSI0 is expressed as an accumulated value of port preset values, and WCi is expressed as a preset standard temperature difference value;
s53: matching the credit value with a preset standard credit threshold, and if the credit value is not greater than the standard credit threshold, judging that a signal port corresponding to the credit value is not in operation and can be accessed and generating a first credit signal; marking the signal port as an active port according to a first signal; if the credit value is greater than the standard credit threshold value, judging that the signal port corresponding to the credit value is running and can not be accessed, and generating a second credit signal; marking the signal port as an invalid port according to the second signal;
s54: and combining the first signal and the second signal and the corresponding valid port and invalid port to obtain a signal analysis set.
6. The big-data-based signal access method according to claim 5, wherein the information request analysis set and the information operation analysis set are simultaneously matched to obtain a matching result, and the specific steps include:
s61: receiving a message request analysis set and a message and motion analysis set and carrying out simultaneous analysis;
s62: matching a port sequencing set in the signal request analysis set with a plurality of effective ports in the signal operation analysis set, and setting the port sequencing set as a selected port if the port sequencing set has signal ports which are the same as the effective ports; if the port sorting set does not have the signal port same as the effective port, judging that the effective port is not matched with the signal port in the port sorting set and generating a first matching signal;
s63: matching a port sequencing set in a message request analysis set with a plurality of effective ports in a message operation analysis set according to a first matching signal, and setting the port sequencing set as a port to be selected if a signal port identical to an invalid port exists in the port sequencing set; if the signal port which is the same as the invalid port does not exist in the port sequencing set, judging that the invalid port is not matched with the signal port in the port sequencing set and generating a second matching signal; generating a re-access prompt according to the second matching signal;
s64: acquiring the state of a port to be selected, and if the state is an operating state, generating a waiting signal to enable signal request data to wait and access; and if the state is a fault state, generating a return signal to enable the signal request data to be applied for access again.
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