CN113765723A - 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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CN113765723A
CN113765723A CN202111116634.XA CN202111116634A CN113765723A CN 113765723 A CN113765723 A CN 113765723A CN 202111116634 A CN202111116634 A CN 202111116634A CN 113765723 A CN113765723 A CN 113765723A
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index
health diagnosis
real
historical
data
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CN113765723B (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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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

Abstract

The invention provides a health diagnosis method and system based on Cable Modem terminal equipment, wherein 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 value table and a CM historical health diagnosis report threshold value 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 value 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 value table, outputting the ratio or index mean value of an index sample over threshold value to obtain a CM historical health diagnosis report. The system of the present invention is applied to the above method. The invention can improve the real-time diagnosis capability of the CM network index and can provide a 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 traditional network indexes of Cable modems (hereinafter, referred to as "operators") of radio and television operators (hereinafter, referred to as "operators") include CM online state, uplink transmission level, uplink SNR, Uplink Codeword Error Rate (UCER), downlink reception level and downlink MER, although the indexes can well display the existence of problems in HFC networks, the operators can only query the current network indexes of the CMs in real time at present, but are difficult to comprehensively analyze historical index data of the CMs, and cannot well reveal the reasons of the problems, as shown in fig. 1, fig. 1 is a schematic diagram of the traditional network indexes of the CMs.
The current operator acquires a CM IP distributed by a CMTS DHCP service when the CM is on line, acquires real-time data of CM network indexes through an SNMP protocol, wherein the real-time data comprises a CM on-line state, an uplink transmitting level, an uplink SNR, an uplink code word error rate (UCER), a downlink receiving level and a downlink MER, and judges the running state of the CM indexes through comparing the real-time data with an index threshold value, wherein the running state comprises a healthy state, a sub-healthy state and a bad state. As shown in fig. 2, fig. 2 is a schematic diagram of CM real-time index acquisition and threshold determination.
Although the real-time diagnosis of the CM network index is realized at present, the network index is limited to the traditional index, the threshold value of the network index is not refined enough, the diagnosis of the network index lacks the correlation analysis with the CMTS uplink port index, and the comprehensive analysis of the historical data of the CM network index lacks, so that the prior art cannot well disclose the reason of the CM network problem.
Disclosure of Invention
The invention mainly aims to provide a health diagnosis method based on Cable Modem terminal equipment, which can improve the real-time diagnosis capability of CM network indexes and can provide health diagnosis reports of the CM network indexes.
The invention also 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 above main object, the present invention provides a health diagnosis method based on Cable Modem terminal equipment, which includes 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; 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; and analyzing the index data based on the CM historical health diagnosis model and the CM historical health diagnosis report threshold value table, and outputting the ratio or the index mean value of the index sample exceeding the threshold value to obtain the CM historical health diagnosis report.
Further, 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 established, CM real-time network index data are collected, the CM real-time health diagnosis model is established 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 a CM uplink emission level, a CM uplink MTR index, a CM uplink SNR, a CM downlink receiving level, a CM downlink MER, a CM downlink bandwidth utilization index, an uplink port SNR index, an uplink port utilization index and a 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.
The method comprises the steps of establishing a first operation and maintenance knowledge base after CM real-time health diagnosis data are obtained, analyzing fault reasons and possible fault phenomena by combining CM real-time health diagnosis index details and CM real-time health diagnosis data to obtain fault reasons and possible fault information results of CM real-time health diagnosis abnormal indexes, 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.
According to a further scheme, after a CM historical health diagnosis report is obtained, a second operation and maintenance knowledge base is established based on the CM historical health diagnosis report, fault reasons and possible fault phenomena are analyzed by combining CM historical index sample data and CM historical health diagnosis report data, and then fault reasons and possible fault information results of abnormal indexes of the CM historical health diagnosis report can be obtained, wherein the second operation and maintenance knowledge base comprises an index abnormal fault reason tree and a fault phenomenon tree.
In a further aspect, the CM historical health diagnosis report threshold table includes a CM termination index and a CMTS uplink port diagnosis index, where an index fluctuation rate, an index deviation rate, and an index mean value are derived from the CM termination index, and an index fluctuation rate, an index deviation rate, and an index maximum value are derived from the CMTS uplink port index.
Further, the calculation formula of the index fluctuation rate 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 for which the fluctuation amplitude of the X index meets the fluctuation threshold, and X (tn) is the total number of collected samples for the X index, and if X (fr) > is 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 index X, X (dn) is the number of times of samples with deviation amplitude meeting the deviation threshold value of the index X, and X (tn) is the total number of times of collecting samples of the index X, and if X (dr) > is 5%, the index has reached the deviation.
In a further scheme, 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, X1, X2, X3 and X4., and Xn is the sampling value of the X indexes.
Further, the calculation formula of the maximum value of the index 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., and Xn is the sampling value of the X index.
In order to achieve another object, the present invention provides a health diagnosis system based on Cable Modem terminal equipment, including: the data acquisition unit is used for acquiring CM network index data; the model building unit is used for building a CM real-time health diagnosis model and a CM historical health diagnosis model according to the obtained 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; and 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 value table, outputting the ratio or the index mean value of the index sample exceeding the threshold value, and obtaining the CM historical health diagnosis report.
Therefore, the uplink pre-equalization coefficient based on the DOCSIS increases the following indexes on the basis of the traditional network indexes: the uplink MTR index, the CM 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 evidences of network problems for the health diagnosis of the terminal by an operator, so that the real-time diagnosis capability of the CM network index is improved; the invention can comprehensively analyze the historical data of the CM network indexes, and the system collects the network index data of each CM as an analysis sample according to the natural period (7 days), thereby outputting a health diagnosis report for the CM in the whole network of an operator and providing high-efficiency data support for the operator to carry out active network operation and maintenance of a user.
Therefore, the invention is beneficial to operators to utilize intelligent monitoring tools, improves the maintenance level, better observes the problem of the terminal network and improves the reliability of the network; the invention applies an active network operation and maintenance strategy, combines operation and maintenance experience and combines other parameters of equipment to establish an efficient CM terminal equipment health diagnosis model, and can identify and solve the problem of the equipment; the invention has the main achievements of reducing the time for troubleshooting and solving problems and reducing the operation cost.
In addition, improvements in network reliability have led to the introduction of services and premium services, thereby generating new revenue, and the invention increases the ability to detect and resolve problems, helping to reduce customer churn.
Drawings
Fig. 1 is a schematic diagram of a conventional network index of a CM in the prior art.
FIG. 2 is a diagram of CM real-time index acquisition 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 according to the present invention.
FIG. 4 is a schematic diagram of a CM real-time health diagnosis index in an embodiment of a health diagnosis method based on Cable Modem terminal devices of the present invention.
FIG. 5 is a schematic diagram of acquiring CM real-time health diagnosis data in an embodiment of the health diagnosis method based on Cable Modem terminal device of the present invention.
FIG. 6 is a schematic diagram of a report index related to historical health diagnosis of CM in an embodiment of a health diagnosis method based on Cable Modem terminal equipment of the present invention.
FIG. 7 is a schematic diagram of obtaining a historical health diagnosis report of CM in an embodiment of the health diagnosis method based on Cable Modem terminal device of the present invention.
FIG. 8 is a schematic diagram of a system platform in an embodiment of a health diagnosis system based on Cable Modem terminal devices according to the present invention.
FIG. 9 is a schematic diagram of an embodiment of a health diagnosis system based on Cable Modem terminal equipment according to the present invention.
The invention is further explained with reference to the drawings and the embodiments.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below. It should be noted that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments, and all other embodiments obtained by those skilled in the art without any inventive work are within the scope of the present invention.
An embodiment of a health diagnosis method based on Cable Modem terminal equipment comprises the following steps:
referring to fig. 1 to 7, a Cable Modem terminal device-based health diagnosis method includes the following steps:
step S1, CM network index data is acquired.
And step S2, constructing a CM real-time health diagnosis model and a CM historical health diagnosis model according to the acquired data.
Step S3, a CM real-time health diagnostic threshold table and a CM historical health diagnostic report threshold table are established.
And step 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 value table to obtain CM real-time health diagnosis data.
And step S5, analyzing the index data based on the CM historical health diagnosis model and the CM historical health diagnosis report threshold value table, and outputting the ratio or the index mean value of the index sample exceeding the 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 historical network index data; when a CM real-time health diagnosis model is established, CM real-time network index data are collected, the CM real-time health diagnosis model is established 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 a CM uplink emission level, a CM uplink MTR index, a CM uplink SNR, a CM downlink receiving level, a CM downlink MER, a CM downlink bandwidth utilization index, an uplink port SNR index, an uplink port utilization index and a 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.
In step S4, after the CM real-time health diagnosis data is obtained, a first operation and maintenance knowledge base is established, and the health diagnosis indexes are in poor and extremely poor levels by combining the CM real-time health diagnosis index details and the CM real-time health diagnosis data, 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, where 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 step S5, 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 the failure cause and possible failure phenomenon are analyzed in combination with the CM historical index sample data and the CM historical health diagnosis report data, so that the failure cause and possible failure information result of each index abnormality of the CM historical health diagnosis report can be obtained, where the second operation and maintenance knowledge base includes an index abnormality failure cause tree and a failure phenomenon tree.
In this embodiment, the CM historical health diagnosis report threshold table includes a CM terminal indicator and a CMTS uplink port diagnosis indicator, where an indicator fluctuation rate, an indicator deviation rate, and an indicator mean value are derived from the CM terminal indicator, and an indicator fluctuation rate, an indicator deviation rate, and an indicator maximum value are derived from the CMTS uplink port indicator.
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 for which the fluctuation amplitude of the X index meets the fluctuation threshold, and X (tn) is the total number of collected samples for the X index, and if X (fr) > is 5%, the index has reached the fluctuation.
In the present embodiment, the calculation formula of the index deviation ratio is expressed as formula (2):
X(DR)＝X(DN)/X(TN)*100％ (2)
wherein, X (dr) is the deviation rate of the index X, X (dn) is the number of times of samples with deviation amplitude meeting the deviation threshold value of the index X, and X (tn) is the total number of times of collecting samples of the index X, and if X (dr) > is 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 X indexes, X1, X2, X3 and X4., and Xn is the sampling value of the X indexes.
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., and Xn is the sampling value of the X index.
As shown in fig. 8, the present invention uses Spring closed distributed cluster to build a system platform, so as to implement independent operation of front-end and back-end separation, data cluster storage, data processing, and data acquisition and analysis.
In this embodiment, the process of acquiring the CM real-time health diagnosis data includes the following steps:
and collecting CM real-time network index data.
And (4) establishing a CM real-time health diagnosis model by the system platform to obtain CM real-time health diagnosis index details.
The system platform establishes a CM real-time health diagnosis threshold table, and divides the CM real-time network index health diagnosis into 5 grades, namely excellent, good, medium, poor and extremely poor.
And analyzing the health diagnosis state of the CM through the CM real-time health diagnosis index detail and the 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 a CM real-time health diagnosis index abnormal fault reason tree and a fault phenomenon tree, the health diagnosis indexes are in poor and extremely poor grades, the fault reason and the possible fault phenomenon are analyzed, and the fault reason and the possible fault information result of the CM real-time health diagnosis abnormal index are finally obtained by combining the CM real-time health diagnosis index detail and the CM real-time health diagnosis data.
The CM index health diagnosis levels of this embodiment include excellent, good, medium (general), poor, and extremely poor, and the threshold values of the CM real-time health diagnosis indexes are as follows:
Figure BDA0003275572490000081
Figure BDA0003275572490000091
TABLE 1
The CM index health diagnosis of the present embodiment can analyze the failure phenomenon corresponding to the poor grade and the extremely poor grade, as shown in table 2 below:
Figure BDA0003275572490000092
Figure BDA0003275572490000101
TABLE 2
In this embodiment, the process of obtaining the CM historical health diagnosis report includes the following steps:
and acquiring historical network index data of the CM.
And the system platform establishes a CM historical index data health diagnosis model, including a data analysis period and index items, and obtains sample data of each CM historical index.
The system platform establishes a CM health diagnosis report threshold table which comprises a CM terminal index and a CMTS (Cable modem termination System) uplink port diagnosis index, wherein the CM terminal index derives an index fluctuation rate, an index deviation rate and an index mean value, and the CMTS uplink port index derives the index fluctuation rate, the index deviation rate and an index maximum value.
And analyzing the indexes through the CM historical index sample data and the CM health diagnosis threshold value table and diagnosis indexes, outputting the index sample over-threshold ratio or index average value, and finally obtaining a CM historical health diagnosis report.
And the system platform establishes an operation and maintenance expert knowledge base related to the CM historical health diagnosis report, wherein the operation and maintenance expert knowledge base comprises an index abnormal fault reason tree and a fault phenomenon tree, analyzes the fault reason and the possible fault phenomenon, and finally obtains the fault reason and the possible fault information result of each index abnormality of the CM historical health diagnosis report by combining the CM historical index sample data and the CM historical health diagnosis report data.
The CM historical health diagnostic report indicator thresholds of this embodiment are as follows in table 3:
Figure BDA0003275572490000111
table 3 the CM historical health diagnostic report indicators for this example are illustrated in table 4 below:
Figure BDA0003275572490000112
Figure BDA0003275572490000121
TABLE 4
The CM historical health diagnosis report of this embodiment may implement analysis of the fault phenomenon corresponding to the index, as shown in table 5 below:
Figure BDA0003275572490000122
Figure BDA0003275572490000131
TABLE 5
Therefore, the uplink pre-equalization coefficient based on the DOCSIS increases the following indexes on the basis of the traditional network indexes: the uplink MTR index, the CM 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 evidences of network problems for the health diagnosis of the terminal by an operator, so that the real-time diagnosis capability of the CM network index is improved; the invention can comprehensively analyze the historical data of the CM network indexes, and the system collects the network index data of each CM as an analysis sample according to the natural period (7 days), thereby outputting a health diagnosis report for the CM in the whole network of an operator and providing high-efficiency data support for the operator to carry out active network operation and maintenance of a user.
Therefore, the invention is beneficial to operators to utilize intelligent monitoring tools, improves the maintenance level, better observes the problem of the terminal network and improves the reliability of the network; the invention applies an active network operation and maintenance strategy, combines operation and maintenance experience and combines other parameters of equipment to establish an efficient CM terminal equipment health diagnosis model, and can identify and solve the problem of the equipment; the invention has the main achievements of reducing the time for troubleshooting and solving problems and reducing the operation cost.
In addition, improvements in network reliability have led to the introduction of services and premium services, thereby generating new revenue, and the invention increases the ability to detect and resolve problems, helping to reduce customer churn.
An embodiment of a health diagnosis system based on Cable Modem terminal equipment comprises:
as shown in fig. 3, the health diagnosis system based on Cable Modem terminal device provided by the present invention is applied to the health diagnosis method based on Cable Modem terminal device, and includes:
a data obtaining unit 10, configured to obtain CM network index data.
And the model building unit 20 is used for building a CM real-time health diagnosis model and a CM historical health diagnosis model according to the obtained data.
And a threshold value table establishing unit 30, configured to establish a CM real-time health diagnosis threshold value table and a CM historical health diagnosis report threshold value table.
And the real-time health diagnosis unit 40 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.
And the historical health diagnosis report generating unit 50 is used for analyzing the index data based on the CM historical health diagnosis model and the CM historical health diagnosis report threshold value table, and outputting the ratio or the index mean value of the index sample exceeding the 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 historical network index data; when a CM real-time health diagnosis model is established, CM real-time network index data are collected, the CM real-time health diagnosis model is established 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 a CM uplink emission level, a CM uplink MTR index, a CM uplink SNR, a CM downlink receiving level, a CM downlink MER, a CM downlink bandwidth utilization index, an uplink port SNR index, an uplink port utilization index and a 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.
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 poor and extremely poor grades, and the fault reasons and possible fault phenomena are analyzed, so that 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.
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, fault reasons and possible fault phenomena are analyzed by combining CM historical index sample data and CM historical health diagnosis report data, and then fault reasons and possible fault information results of all index abnormalities 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 historical health diagnosis report threshold table includes a CM terminal indicator and a CMTS uplink port diagnosis indicator, where an indicator fluctuation rate, an indicator deviation rate, and an indicator mean value are derived from the CM terminal indicator, and an indicator fluctuation rate, an indicator deviation rate, and an indicator maximum value are derived from the CMTS uplink port indicator.
It can be seen that the DOCSIS protocol can be used by the present invention as more and more intelligent terminal devices are deployed in HFC networks, such as digital Set Top Boxes (STBs), Multimedia Terminal Adapters (MTAs) and embedded MTAs, even high-end televisions. Therefore, the uplink pre-equalization coefficient based on the DOCSIS of the invention is added with the following indexes on the basis of the traditional network indexes: the uplink MTR index, the CM 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 evidences of network problems for the health diagnosis of the terminal by an operator, and the real-time diagnosis capability of the CM network index can be improved.
In addition, as the operator HFC network has been developed, many different services are performed on the HFC network, such as telephone, data, video, commercial and advanced services (e.g., telemedicine, teleeducation, home monitoring), and thus the demand of the radio and television operator (hereinafter referred to as "operator") for maintaining high reliability of services has increased, and in order to achieve such high reliability, the operator should solve the problem before any influence is exerted on the services. Therefore, the invention comprehensively analyzes the historical data of the CM network indexes, and the system acquires the network index data of each CM as an analysis sample according to the natural period (7 days), thereby outputting a health diagnosis report for the CM in the whole network of an operator and providing efficient data support for the operator to carry out active network operation and maintenance of a user.
It should be noted that reference throughout this specification to "one embodiment," "another embodiment," "an embodiment," "a preferred embodiment," or the like, means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment described generally in this application. The appearances of the same 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 submitted that it is within the purview of one skilled in the art to effect such feature, structure, or characteristic in connection with other ones of the embodiments. Although the invention 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 specifically, other uses will be apparent to those skilled in the art in view of variations and modifications in the subject matter incorporating the components and/or arrangement of the arrangement within the scope of the disclosure, drawings and claims hereof.

Claims (10)

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;
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;
and analyzing the index data based on the CM historical health diagnosis model and the CM historical health diagnosis report threshold value table, and outputting the ratio or the index mean value of the index sample exceeding the threshold value to obtain the CM historical health diagnosis report.
2. The method of claim 1, wherein:
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 established, CM real-time network index data are collected, the CM real-time health diagnosis model is established 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 a CM uplink emission level, a CM uplink MTR index, a CM uplink SNR, a CM downlink receiving level, a CM downlink MER, a CM downlink bandwidth utilization index, an uplink port SNR index, an uplink port utilization index and a 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.
3. The method of claim 2, wherein:
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 poor and extremely poor grades, and the fault reasons and possible fault phenomena are analyzed, so that 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.
4. The method of claim 3, wherein:
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, fault reasons and possible fault phenomena are analyzed by combining CM historical index sample data and CM historical health diagnosis report data, and the fault reason and possible fault information results of the CM historical health diagnosis report with abnormal indexes can be obtained, wherein the second operation and maintenance knowledge base comprises an index abnormal fault reason tree and a fault phenomenon tree.
5. The method according to any one of claims 1 to 4, characterized in that:
the CM historical health diagnosis report threshold table comprises CM terminal indexes and CMTS uplink port diagnosis indexes, wherein index fluctuation rates, index deviation rates and index mean values are derived from the CM terminal indexes, and index fluctuation rates, index deviation rates and index maximum values are derived from the CMTS uplink port indexes.
6. The method of claim 5, wherein:
the calculation formula of the index fluctuation rate 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 for which the fluctuation amplitude of the X index meets the fluctuation threshold, and X (tn) is the total number of collected samples for the X index, and if X (fr) > is 5%, the index has reached the fluctuation.
7. The method of claim 5, wherein:
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 index X, X (dn) is the number of times of samples with deviation amplitude meeting the deviation threshold value of the index X, and X (tn) is the total number of times of collecting samples of the index X, and if X (dr) > is 5%, the index has reached the deviation.
8. The method of claim 5, wherein:
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, X1, X2, X3 and X4., and Xn is the sampling value of the X indexes.
9. The method of claim 5, wherein:
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., and Xn is the sampling value of the X index.
10. A health diagnosis system based on Cable Modem terminal equipment is characterized by comprising:
the data acquisition unit is used for acquiring CM network index data;
the model building unit is used for building a CM real-time health diagnosis model and a CM historical health diagnosis model according to the obtained 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;
and 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 value table, outputting the ratio or the index mean value of the index sample exceeding the threshold value, and obtaining the CM historical health diagnosis report.
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