CN113765723B - Health diagnosis method and system based on Cable Modem terminal equipment - Google Patents

Health diagnosis method and system based on Cable Modem terminal equipment Download PDF

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CN113765723B
CN113765723B CN202111116634.XA CN202111116634A CN113765723B CN 113765723 B CN113765723 B CN 113765723B CN 202111116634 A CN202111116634 A CN 202111116634A CN 113765723 B CN113765723 B CN 113765723B
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health diagnosis
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data
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CN113765723A (en
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雷振
邱灿波
章亦农
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Shenzhen Print Rite Network Engineering Co ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/04—Processing captured monitoring data, e.g. for logfile generation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/06—Management of faults, events, alarms or notifications
    • H04L41/0631—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/142—Network analysis or design using statistical or mathematical methods
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/06—Generation of reports
    • H04L43/065—Generation of reports related to network devices
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/16—Threshold monitoring

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Abstract

The invention provides a health diagnosis method and a system thereof based on Cable Modem terminal equipment, the method comprises the steps of obtaining CM network index data, constructing a CM real-time health diagnosis model and a CM historical health diagnosis model according to the obtained data, establishing a CM real-time health diagnosis threshold table and a CM historical health diagnosis report threshold table, analyzing the health diagnosis state of the CM terminal equipment based on the CM real-time health diagnosis model and the CM real-time health diagnosis threshold table to obtain CM real-time health diagnosis data, analyzing the index data based on the CM historical health diagnosis model and the CM historical health diagnosis report threshold table, and outputting the duty ratio or index mean value of an index sample exceeding a threshold value to obtain a CM historical health diagnosis report. The system of the present invention is applied to the above-described method. The invention can improve the capability of real-time diagnosis of the CM network index and can provide the health diagnosis report of the CM network index.

Description

Health diagnosis method and system based on Cable Modem terminal equipment
Technical Field
The invention relates to the technical field of data analysis, in particular to a health diagnosis method based on Cable Modem terminal equipment and a system applying the method.
Background
The conventional network indexes of the Cable Modem (hereinafter referred to as CM) by the broadcast and television operator (hereinafter referred to as "operator") include the on-line state of the CM, the uplink transmitting level, the uplink SNR, the Uplink Codeword Error Rate (UCER), the downlink receiving level and the downlink MER, and although these indexes can well show the existence of the problems in the HFC network, the current network indexes of the CM can only be queried in real time by the operator at present, but the historical index data of the CM is difficult to comprehensively analyze, and the reasons for the problems cannot be well revealed, as shown in fig. 1, fig. 1 is a schematic diagram of the conventional network indexes of the CM.
At present, an operator acquires CM IP distributed by CMTS DHCP service when the CM is on line, acquires real-time data of CM network indexes including CM on-line state, uplink transmitting level, uplink SNR, uplink Codeword Error Rate (UCER), downlink receiving level and downlink MER through SNMP protocol, and judges the running state of the CM indexes including health, sub-health and bad state through comparison of the real-time data and index threshold. As shown in fig. 2, fig. 2 is a schematic diagram of CM real-time index collection and threshold judgment.
At present, although real-time diagnosis of CM network indexes is realized, the network indexes are limited to traditional indexes, the threshold values of the network indexes are not refined enough, and the diagnosis of the network indexes and the correlation analysis of CMTS uplink port indexes are lack, and the comprehensive analysis of CM network index historical data is lack, so that the prior art cannot well reveal the cause of CM network problems.
Disclosure of Invention
The invention mainly aims to provide a health diagnosis method based on Cable Modem terminal equipment, which can improve the capability of real-time diagnosis of CM network indexes and can provide health diagnosis reports of CM network indexes.
The invention further aims to provide a health diagnosis system based on the Cable Modem terminal device, which is applied to the method.
In order to achieve the main purpose, the invention provides a health diagnosis method based on Cable Modem terminal equipment, which comprises the following steps: acquiring CM network index data; constructing a CM real-time health diagnosis model and a CM historical health diagnosis model according to the acquired data; establishing a CM real-time health diagnosis threshold value table and a CM historical health diagnosis report threshold value table; based on the CM real-time health diagnosis model and the CM real-time health diagnosis threshold table, analyzing the health diagnosis state of the CM terminal equipment to obtain CM real-time health diagnosis data; and analyzing the index data based on the CM historical health diagnosis model and the CM historical health diagnosis report threshold table, and outputting the duty ratio or the index mean value of the super-threshold of the index sample to obtain the CM historical health diagnosis report.
Further, the CM network index data includes CM real-time network index data and CM history network index data; when a CM real-time health diagnosis model is built, CM real-time network index data are collected, the CM real-time health diagnosis model is built according to the index data, and CM real-time health diagnosis index details are obtained, wherein the CM real-time health diagnosis index details comprise CM uplink emission level, CM uplink MTR index, CM uplink SNR, CM downlink receiving level, CM downlink MER, CM downlink bandwidth utilization index, uplink port SNR index, uplink port utilization index and downlink port utilization index; and when the CM historical health diagnosis model is built, acquiring CM historical network index data, building the CM historical health diagnosis model according to the index data, and obtaining sample data of each CM historical index.
After the CM real-time health diagnosis data is obtained, a first operation and maintenance knowledge base is established, the CM real-time health diagnosis index detail and the CM real-time health diagnosis data are combined, the health diagnosis indexes are in bad and extremely bad grades, the fault reasons and possible fault phenomena are analyzed, and the fault reasons and possible fault information results of the CM real-time health diagnosis abnormal indexes can be obtained, wherein the first operation and maintenance knowledge base comprises a CM real-time health diagnosis index abnormal fault reason tree and a CM real-time health diagnosis index abnormal fault phenomenon tree.
After the CM historical health diagnosis report is obtained, a second operation and maintenance knowledge base is established based on the CM historical health diagnosis report, and fault reasons and possible fault phenomena are analyzed by combining CM historical index sample data and CM historical health diagnosis report data, so that fault reasons and possible fault information results of each index abnormality of the CM historical health diagnosis report can be obtained, wherein the second operation and maintenance knowledge base comprises an index abnormality fault reason tree and a fault phenomenon tree.
In a further aspect, the CM historical health diagnosis report threshold table includes a CM terminal indicator and a CMTS upstream port diagnosis indicator, where the CM terminal indicator derives an indicator fluctuation rate, an indicator deviation rate, and an indicator mean value, and the CMTS upstream port indicator derives an indicator fluctuation rate, an indicator deviation rate, and an indicator maximum value.
In a further aspect, the calculation formula of the index fluctuation ratio is expressed as formula (1):
X(FR)＝X(FN)/X(TN)*100％ (1)
Wherein X (FR) is the fluctuation rate of the X index, X (FN) is the number of samples whose X index fluctuation amplitude meets the fluctuation threshold, X (TN) is the total number of samples collected by the X index, and if X (FR) > =5%, the index has reached the fluctuation.
Further, the calculation formula of the index deviation rate is expressed as formula (2):
X(DR)＝X(DN)/X(TN)*100％ (2)
wherein X (DR) is the deviation rate of the X index, X (DN) is the number of samples of which the X index deviation amplitude meets the deviation threshold, and X (TN) is the total number of samples collected by the X index, and if X (DR) > =5%, the index has reached the deviation.
In a further aspect, the calculation formula of the index mean value is expressed as formula (3):
X(AVG)＝∑(X1,X2,X3,X4...,Xn)/n (3)
Wherein X (AVG) is the mean value of the X index, and X1, X2, X3, X4..
Still further, the calculation formula of the index maximum value is expressed as formula (4):
X(MAX)＝Max(X1,X2,X3,X4...,Xn) (4)
Wherein X (MAX) is the mean value of the X index, X1, X2, X3, X4..
In order to achieve the other object, the present invention provides a health diagnosis system based on Cable Modem terminal equipment, including: a data acquisition unit for acquiring CM network index data; the model construction unit is used for constructing a CM real-time health diagnosis model and a CM historical health diagnosis model according to the acquired data; the threshold value table establishing unit is used for establishing a CM real-time health diagnosis threshold value table and a CM historical health diagnosis report threshold value table; the real-time health diagnosis unit is used for analyzing the health diagnosis state of the CM terminal equipment based on the CM real-time health diagnosis model and the CM real-time health diagnosis threshold value table to obtain CM real-time health diagnosis data; the historical health diagnosis report generating unit is used for analyzing the index data based on the CM historical health diagnosis model and the CM historical health diagnosis report threshold table, outputting the duty ratio or the index mean value of the index sample super-threshold value and obtaining the CM historical health diagnosis report.
Therefore, the invention increases the following indexes based on the traditional network indexes based on the uplink pre-equalization coefficient of DOCSIS: the uplink MTR index, the downlink bandwidth utilization index, the uplink port SNR index, the uplink port utilization index and the downlink port utilization index of the CM provide more evidence of network problems for operators to diagnose the health of the terminal, thereby improving the capability of real-time diagnosis of the CM network index; the invention can comprehensively analyze the CM network index historical data, the system can take the network index data of each CM collected in the natural week (7 days) as an analysis sample, and can output a health diagnosis report for the CM of the whole network of an operator, thereby providing high-efficiency data support for the operator to realize the active network operation and maintenance of the user.
Therefore, the invention is beneficial to operators to utilize intelligent monitoring tools, improves the maintenance level, better insights the problem of terminal network and improves the network reliability; the invention applies the active network operation and maintenance strategy, combines operation and maintenance experience with other parameters of equipment, establishes the efficient CM terminal equipment health diagnosis model, and can identify and solve the equipment problems; the main achievement of the invention is to reduce the time for troubleshooting and solving the problems and reduce the operation cost.
In addition, the improvement in network reliability has led to the introduction of business and premium services, thereby generating new revenue, which increases the ability to detect and solve problems, helping to reduce customer churn.
Drawings
Fig. 1 is a schematic diagram of a CM conventional network index in the prior art.
Fig. 2 is a schematic diagram of CM real-time index collection and threshold values in the prior art.
Fig. 3 is a flowchart of an embodiment of a health diagnosis method based on Cable Modem terminal equipment.
Fig. 4 is a schematic diagram of a real-time health diagnosis index about CM in an embodiment of a health diagnosis method based on Cable Modem terminal equipment according to the present invention.
Fig. 5 is a schematic diagram of acquiring CM real-time health diagnosis data in an embodiment of a health diagnosis method based on a Cable Modem terminal device according to the present invention.
Fig. 6 is a schematic diagram of a CM history health diagnosis report indicator according to an embodiment of a health diagnosis method based on a Cable Modem terminal device of the present invention.
Fig. 7 is a schematic diagram of a health diagnosis method based on Cable Modem terminal equipment according to an embodiment of the present invention, regarding obtaining a CM history health diagnosis report.
Fig. 8 is a schematic diagram of a system platform in an embodiment of a health diagnosis system based on Cable Modem terminal equipment of the present invention.
Fig. 9 is a schematic diagram of an embodiment of a health diagnosis system based on Cable Modem terminal equipment of the present invention.
The invention is further described below with reference to the drawings and examples.
Detailed Description
In order to make the above objects, features and advantages of the present invention more comprehensible, the following detailed description of the technical solution of the present invention refers to the accompanying drawings and specific embodiments. It should be noted that the described embodiments are only some embodiments of the present invention, and not all embodiments, and that all other embodiments obtained by persons skilled in the art without making creative efforts based on the embodiments in the present invention are within the protection scope of the present invention.
Health diagnosis method embodiment based on Cable Modem terminal equipment:
referring to fig. 1 to 7, a health diagnosis method based on Cable Modem terminal equipment, the method comprises the following steps:
Step S1, obtaining CM network index data.
And S2, constructing a CM real-time health diagnosis model and a CM historical health diagnosis model according to the acquired data.
And step S3, a CM real-time health diagnosis threshold value table and a CM historical health diagnosis report threshold value table are established.
And S4, analyzing the health diagnosis state of the CM terminal equipment based on the CM real-time health diagnosis model and the CM real-time health diagnosis threshold table to obtain CM real-time health diagnosis data.
And S5, analyzing the index data based on the CM historical health diagnosis model and the CM historical health diagnosis report threshold table, and outputting the duty ratio or the index mean value of the index sample super-threshold value to obtain the CM historical health diagnosis report.
In this embodiment, the CM network index data includes CM real-time network index data and CM history network index data; when the CM real-time health diagnosis model is built, CM real-time network index data are collected, a CM real-time health diagnosis model is built according to the index data, and CM real-time health diagnosis index details are obtained, wherein the CM real-time health diagnosis index details comprise CM uplink emission level, CM uplink MTR index, CM uplink SNR, CM downlink receiving level, CM downlink MER, CM downlink bandwidth utilization index, uplink port SNR index, uplink port utilization index and downlink port utilization index; and when the CM historical health diagnosis model is built, acquiring CM historical network index data, building the CM historical health diagnosis model according to the index data, and obtaining sample data of each CM historical index.
In the step S4, after obtaining the CM real-time health diagnosis data, a first operation and maintenance knowledge base is established, and the CM real-time health diagnosis index details and the CM real-time health diagnosis data are combined, the health diagnosis indexes are in the bad and very bad grades, and the fault cause and the possible fault phenomenon are analyzed, so that the fault cause and the possible fault information result of the CM real-time health diagnosis abnormal index can be obtained, wherein the first operation and maintenance knowledge base includes a CM real-time health diagnosis index abnormal fault cause tree and a fault phenomenon tree.
In the step S5, after the CM history health diagnosis report is obtained, a second operation and maintenance knowledge base is established based on the CM history health diagnosis report, and the fault cause and the possible fault phenomenon are analyzed by combining the CM history index sample data and the CM history health diagnosis report data, so as to obtain the fault cause and the possible fault information result of each index abnormality of the CM history health diagnosis report, wherein the second operation and maintenance knowledge base includes an index abnormality fault cause tree and a fault phenomenon tree.
In this embodiment, the CM history health diagnosis report threshold table includes a CM terminal index and a CMTS upstream port diagnosis index, where the CM terminal index derives an index fluctuation rate, an index deviation rate, and an index average value, and the CMTS upstream port index derives an index fluctuation rate, an index deviation rate, and an index maximum value.
In the present embodiment, the calculation formula of the index fluctuation ratio is expressed as formula (1):
X(FR)＝X(FN)/X(TN)*100％ (1)
Wherein X (FR) is the fluctuation rate of the X index, X (FN) is the number of samples whose X index fluctuation amplitude meets the fluctuation threshold, X (TN) is the total number of samples collected by the X index, and if X (FR) > =5%, the index has reached the fluctuation.
In the present embodiment, the calculation formula of the index deviation rate is expressed as formula (2):
X(DR)＝X(DN)/X(TN)*100％ (2)
wherein X (DR) is the deviation rate of the X index, X (DN) is the number of samples of which the X index deviation amplitude meets the deviation threshold, and X (TN) is the total number of samples collected by the X index, and if X (DR) > =5%, the index has reached the deviation.
In the present embodiment, the calculation formula of the index mean value is expressed as formula (3):
X(AVG)＝∑(X1,X2,X3,X4...,Xn)/n (3)
Wherein X (AVG) is the mean value of the X index, and X1, X2, X3, X4..
In the present embodiment, the calculation formula of the index maximum value is expressed as formula (4):
X(MAX)＝Max(X1,X2,X3,X4...,Xn) (4)
Wherein X (MAX) is the mean value of the X index, X1, X2, X3, X4..
As shown in FIG. 8, the invention adopts Spring Clould distributed clusters to build a system platform, and realizes independent operation of front-end and back-end separation, data cluster storage, data processing and data acquisition analysis.
The method of the present invention includes how to obtain CM real-time health diagnosis data and obtain CM history health diagnosis report, in this embodiment, the process of obtaining CM real-time health diagnosis data includes the following steps:
And collecting CM real-time network index data.
And the system platform establishes a CM real-time health diagnosis model to obtain CM real-time health diagnosis index details.
The system platform establishes a CM real-time health diagnosis threshold table, and divides CM real-time network index health diagnosis into 5 grades, namely excellent, good, medium, bad and extremely bad.
And analyzing the CM health diagnosis state through CM real-time health diagnosis index details and a CM real-time health diagnosis threshold value table to obtain CM real-time health diagnosis data.
The system platform establishes an operation and maintenance knowledge base of the CM real-time health diagnosis index abnormal fault cause tree and fault phenomenon tree, analyzes the fault cause and possible fault phenomenon according to the poor and extremely poor grades of the health diagnosis indexes, combines CM real-time health diagnosis index details and CM real-time health diagnosis data, and finally obtains the fault cause and possible fault information result of the CM real-time health diagnosis abnormal index.
The CM index health diagnosis level of this embodiment includes excellent, good, medium (general), poor, very poor, and the threshold values of the CM real-time health diagnosis index are as follows in table 1:
TABLE 1
The CM index health diagnosis of this embodiment can realize the analysis of the fault phenomena corresponding to the difference level and the extremely difference level, as shown in table 2 below:
TABLE 2
In this embodiment, the process of obtaining the CM history health diagnosis report includes the following steps:
and acquiring CM historical network index data.
The system platform establishes a CM historical index data health diagnosis model which comprises a data analysis period and index items, and obtains each CM historical index sample data.
The system platform establishes a CM health diagnosis report threshold table comprising CM terminal indexes and CMTS uplink port diagnosis indexes, wherein the CM terminal indexes derive an index fluctuation rate, an index deviation rate and an index mean value, and the CMTS uplink port indexes derive an index fluctuation rate, an index deviation rate and an index maximum value.
And analyzing the index through the CM historical index sample data, the CM health diagnosis threshold value table and the diagnosis index, outputting the super-threshold value duty ratio of the index sample or the index mean value, and finally obtaining the CM historical health diagnosis report.
The system platform establishes an operation and maintenance expert knowledge base related to the CM historical health diagnosis report, comprises an index abnormal fault cause tree and a fault phenomenon tree, analyzes fault causes and possible fault phenomena, combines CM historical index sample data and CM historical health diagnosis report data, and finally obtains fault causes and possible fault information results of each index abnormality of the CM historical health diagnosis report.
The CM history health diagnosis report index threshold value of the present embodiment is as follows table 3:
table 3 CM history health diagnosis report index of this embodiment is described in table 4 below:
TABLE 4 Table 4
The CM history health diagnosis report of this embodiment can analyze the fault phenomenon corresponding to the index, as shown in table 5 below:
TABLE 5
Therefore, the invention increases the following indexes based on the traditional network indexes based on the uplink pre-equalization coefficient of DOCSIS: the uplink MTR index, the downlink bandwidth utilization index, the uplink port SNR index, the uplink port utilization index and the downlink port utilization index of the CM provide more evidence of network problems for operators to diagnose the health of the terminal, thereby improving the capability of real-time diagnosis of the CM network index; the invention can comprehensively analyze the CM network index historical data, the system can take the network index data of each CM collected in the natural week (7 days) as an analysis sample, and can output a health diagnosis report for the CM of the whole network of an operator, thereby providing high-efficiency data support for the operator to realize the active network operation and maintenance of the user.
Therefore, the invention is beneficial to operators to utilize intelligent monitoring tools, improves the maintenance level, better insights the problem of terminal network and improves the network reliability; the invention applies the active network operation and maintenance strategy, combines operation and maintenance experience with other parameters of equipment, establishes the efficient CM terminal equipment health diagnosis model, and can identify and solve the equipment problems; the main achievement of the invention is to reduce the time for troubleshooting and solving the problems and reduce the operation cost.
In addition, the improvement in network reliability has led to the introduction of business and premium services, thereby generating new revenue, which increases the ability to detect and solve problems, helping to reduce customer churn.
A health diagnosis system embodiment based on Cable Modem terminal equipment:
as shown in fig. 3, the health diagnosis system based on the Cable Modem terminal device provided by the invention is applied to the health diagnosis method based on the Cable Modem terminal device, and comprises the following steps:
a data acquisition unit 10 for acquiring CM network index data.
The model construction unit 20 is configured to construct a CM real-time health diagnosis model and a CM history health diagnosis model based on the acquired data.
A threshold table creation unit 30 for creating a CM real-time health diagnosis threshold table and a CM history health diagnosis report threshold table.
The real-time health diagnosis unit 40 is configured to analyze the health diagnosis status of the CM terminal device based on the CM real-time health diagnosis model and the CM real-time health diagnosis threshold table, and obtain CM real-time health diagnosis data.
The historical health diagnosis report generating unit 50 is configured to analyze the index data based on the CM historical health diagnosis model and the CM historical health diagnosis report threshold table, and output the duty ratio or the index mean of the index sample exceeding the threshold value, so as to obtain a CM historical health diagnosis report.
In this embodiment, the CM network index data includes CM real-time network index data and CM history network index data; when the CM real-time health diagnosis model is built, CM real-time network index data are collected, a CM real-time health diagnosis model is built according to the index data, and CM real-time health diagnosis index details are obtained, wherein the CM real-time health diagnosis index details comprise CM uplink emission level, CM uplink MTR index, CM uplink SNR, CM downlink receiving level, CM downlink MER, CM downlink bandwidth utilization index, uplink port SNR index, uplink port utilization index and downlink port utilization index; and when the CM historical health diagnosis model is built, acquiring CM historical network index data, building the CM historical health diagnosis model according to the index data, and obtaining sample data of each CM historical index.
After the CM real-time health diagnosis data is obtained, a first operation and maintenance knowledge base is established, the CM real-time health diagnosis index detail and the CM real-time health diagnosis data are combined, the health diagnosis indexes are in bad and extremely bad grades, the fault reasons and possible fault phenomena are analyzed, and the fault reasons and possible fault information results of the CM real-time health diagnosis abnormal indexes can be obtained, wherein the first operation and maintenance knowledge base comprises a CM real-time health diagnosis index abnormal fault reason tree and a CM real-time health diagnosis index abnormal fault phenomenon tree.
After the CM historical health diagnosis report is obtained, a second operation and maintenance knowledge base is established based on the CM historical health diagnosis report, and fault reasons and possible fault phenomena are analyzed by combining CM historical index sample data and CM historical health diagnosis report data, so that fault reasons and possible fault information results of each index abnormality of the CM historical health diagnosis report can be obtained, wherein the second operation and maintenance knowledge base comprises an index abnormality fault reason tree and a fault phenomenon tree.
In this embodiment, the CM history health diagnosis report threshold table includes a CM terminal index and a CMTS upstream port diagnosis index, where the CM terminal index derives an index fluctuation rate, an index deviation rate, and an index average value, and the CMTS upstream port index derives an index fluctuation rate, an index deviation rate, and an index maximum value.
It can be seen that the present invention can use DOCSIS protocols with more and more intelligent terminal devices deployed in HFC networks, such as digital Set Top Boxes (STBs), multimedia Terminal Adapters (MTAs), and embedded MTAs, even high-end televisions. Therefore, the invention increases the following indexes based on the traditional network indexes based on the uplink pre-equalization coefficient of DOCSIS: the uplink MTR index, the downlink bandwidth utilization index, the uplink port SNR index, the uplink port utilization index and the downlink port utilization index of the CM provide more evidence of network problems for operators to diagnose the health of the terminal, and can improve the capability of real-time diagnosis of the CM network index.
In addition, as operators' HFC networks develop, many different services are performed on HFC networks, such as telephone, data, video, business and advanced services (e.g., telemedicine, distance education, home monitoring), so the need for high reliability of maintenance services by broadcast and television operators (hereinafter referred to as "operators") is increasing, and in order to achieve such high reliability, operators should solve the problem before any impact on the services is generated. Therefore, the invention comprehensively analyzes the CM network index historical data, the system takes the network index data of each CM collected in the natural week (7 days) as an analysis sample, and outputs a health diagnosis report for the CM of the whole network of the operator, thereby providing high-efficiency data support for the operator to realize the active network operation and maintenance of the user.
It should be noted that references in the specification to "one embodiment," "another embodiment," "an embodiment," "a preferred embodiment," etc., indicate that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the application in general description. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with any embodiment, it is intended to be within the scope of the application to implement such feature, structure, or characteristic in connection with other embodiments. Although the application has been described herein with reference to a number of illustrative examples thereof, it should be understood that numerous other modifications and embodiments can be devised by those skilled in the art that will fall within the scope and spirit of the principles of this disclosure. More particularly, other uses will be apparent to those skilled in the art from consideration of the specification, drawings and claims in connection with the disclosed subject matter and/or other variations and modifications of the component parts and/or arrangements of the subject matter.

Claims (4)

1. A health diagnosis method based on Cable Modem terminal equipment is characterized by comprising the following steps:
Acquiring CM network index data;
constructing a CM real-time health diagnosis model and a CM historical health diagnosis model according to the acquired data;
Establishing a CM real-time health diagnosis threshold value table and a CM historical health diagnosis report threshold value table;
based on the CM real-time health diagnosis model and the CM real-time health diagnosis threshold table, analyzing the health diagnosis state of the CM terminal equipment to obtain CM real-time health diagnosis data;
Analyzing the index data based on the CM historical health diagnosis model and the CM historical health diagnosis report threshold table, and outputting the duty ratio or the index mean value of the index sample super-threshold value to obtain a CM historical health diagnosis report;
the CM network index data comprises CM real-time network index data and CM historical network index data;
When a CM real-time health diagnosis model is built, CM real-time network index data are collected, the CM real-time health diagnosis model is built according to the index data, and CM real-time health diagnosis index details are obtained, wherein the CM real-time health diagnosis index details comprise CM uplink emission level, CM uplink MTR index, CM uplink SNR, CM downlink receiving level, CM downlink MER, CM downlink bandwidth utilization index, uplink port SNR index, uplink port utilization index and downlink port utilization index;
When a CM historical health diagnosis model is established, CM historical network index data are obtained, a CM historical health diagnosis model is established according to the index data, and sample data of each CM historical index are obtained; analyzing the index through the CM historical index sample data, a CM health diagnosis threshold value table and a diagnosis index, and outputting the super-threshold value duty ratio of the index sample or the index mean value to finally obtain a CM historical health diagnosis report, wherein the CM historical health diagnosis report index is described in the following table;
the CM historical health diagnosis report threshold value table comprises CM terminal indexes and CMTS uplink port diagnosis indexes, wherein the CM terminal indexes are used for deriving index fluctuation rates, index deviation rates and index average values, and the CMTS uplink port indexes are used for deriving index fluctuation rates, index deviation rates and index maximum values;
the calculation formula of the index fluctuation ratio is expressed as formula (1):
X(FR)＝X(FN)/X(TN)*100％ (1)
wherein X (FR) is the fluctuation rate of the X index, X (FN) is the number of samples with X index fluctuation amplitude meeting the fluctuation threshold, X (TN) is the total number of samples collected by the X index, and if X (FR) > =5%, the index has reached the fluctuation;
the calculation formula of the index deviation rate is expressed as formula (2):
X(DR)＝X(DN)/X(TN)*100％ (2)
Wherein X (DR) is the deviation rate of the X index, X (DN) is the number of samples of which the X index deviation amplitude accords with the deviation threshold, X (TN) is the total number of samples collected by the X index, and if X (DR) > =5%, the index has reached the deviation;
the calculation formula of the index mean value is expressed as formula (3):
X(AVG)＝∑(X1,X2,X3,X4...,Xn)/n (3)
Wherein X (AVG) is the mean value of X indexes, and X1, X2, X3, X4., and Xn is the sampling value of the X indexes;
the calculation formula of the index maximum value is expressed as formula (4):
X(MAX)＝Max(X1,X2,X3,X4...,Xn) (4)
Wherein X (MAX) is the mean value of the X index, X1, X2, X3, X4..
2. The method according to claim 1, characterized in that:
After the CM real-time health diagnosis data are obtained, a first operation and maintenance knowledge base is established, the CM real-time health diagnosis index detail and the CM real-time health diagnosis data are combined, the health diagnosis indexes are in bad and extremely bad grades, the fault reasons and possible fault phenomena are analyzed, and the fault reasons and possible fault information results of the CM real-time health diagnosis abnormal indexes can be obtained, wherein the first operation and maintenance knowledge base comprises a CM real-time health diagnosis index abnormal fault reason tree and a fault phenomenon tree.
3. The method according to claim 2, characterized in that:
after the CM historical health diagnosis report is obtained, a second operation and maintenance knowledge base is established based on the CM historical health diagnosis report, and fault reasons and possible fault phenomena are analyzed by combining CM historical index sample data and CM historical health diagnosis report data, so that fault reasons and possible fault information results of each index abnormality of the CM historical health diagnosis report can be obtained, wherein the second operation and maintenance knowledge base comprises an index abnormality fault reason tree and a fault phenomenon tree.
4. A health diagnosis system based on Cable Modem terminal equipment is characterized by comprising:
A data acquisition unit for acquiring CM network index data;
The model construction unit is used for constructing a CM real-time health diagnosis model and a CM historical health diagnosis model according to the acquired data;
The threshold value table establishing unit is used for establishing a CM real-time health diagnosis threshold value table and a CM historical health diagnosis report threshold value table;
The real-time health diagnosis unit is used for analyzing the health diagnosis state of the CM terminal equipment based on the CM real-time health diagnosis model and the CM real-time health diagnosis threshold value table to obtain CM real-time health diagnosis data;
the historical health diagnosis report generating unit is used for analyzing the index data based on the CM historical health diagnosis model and the CM historical health diagnosis report threshold table, outputting the duty ratio or the index mean value of the index sample super-threshold value and obtaining the CM historical health diagnosis report;
When a CM real-time health diagnosis model is built, CM real-time network index data are collected, the CM real-time health diagnosis model is built according to the index data, and CM real-time health diagnosis index details are obtained, wherein the CM real-time health diagnosis index details comprise CM uplink emission level, CM uplink MTR index, CM uplink SNR, CM downlink receiving level, CM downlink MER, CM downlink bandwidth utilization index, uplink port SNR index, uplink port utilization index and downlink port utilization index;
When a CM historical health diagnosis model is established, CM historical network index data are obtained, a CM historical health diagnosis model is established according to the index data, and sample data of each CM historical index are obtained; analyzing the index through the CM historical index sample data, a CM health diagnosis threshold value table and a diagnosis index, and outputting the super-threshold value duty ratio of the index sample or the index mean value to finally obtain a CM historical health diagnosis report, wherein the CM historical health diagnosis report index is described in the following table;
the CM historical health diagnosis report threshold value table comprises CM terminal indexes and CMTS uplink port diagnosis indexes, wherein the CM terminal indexes are used for deriving index fluctuation rates, index deviation rates and index average values, and the CMTS uplink port indexes are used for deriving index fluctuation rates, index deviation rates and index maximum values;
the calculation formula of the index fluctuation ratio is expressed as formula (1):
X(FR)＝X(FN)/X(TN)*100％ (1)
wherein X (FR) is the fluctuation rate of the X index, X (FN) is the number of samples with X index fluctuation amplitude meeting the fluctuation threshold, X (TN) is the total number of samples collected by the X index, and if X (FR) > =5%, the index has reached the fluctuation;
the calculation formula of the index deviation rate is expressed as formula (2):
X(DR)＝X(DN)/X(TN)*100％ (2)
Wherein X (DR) is the deviation rate of the X index, X (DN) is the number of samples of which the X index deviation amplitude accords with the deviation threshold, X (TN) is the total number of samples collected by the X index, and if X (DR) > =5%, the index has reached the deviation;
the calculation formula of the index mean value is expressed as formula (3):
X(AVG)＝∑(X1,X2,X3,X4...,Xn)/n (3)
Wherein X (AVG) is the mean value of X indexes, and X1, X2, X3, X4., and Xn is the sampling value of the X indexes;
the calculation formula of the index maximum value is expressed as formula (4):
X(MAX)＝Max(X1,X2,X3,X4...,Xn) (4)
Wherein X (MAX) is the mean value of the X index, X1, X2, X3, X4..
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