CN117395695A

CN117395695A - On-line diagnosis processing system for wireless network

Info

Publication number: CN117395695A
Application number: CN202311379681.2A
Authority: CN
Inventors: 赵先明; 向阳; 林昀
Original assignee: Beijing Hongshan Information Technology Research Institute Co Ltd
Current assignee: Beijing Hongshan Information Technology Research Institute Co Ltd
Priority date: 2023-10-24
Filing date: 2023-10-24
Publication date: 2024-01-12

Abstract

The invention discloses a wireless network on-line diagnosis processing system in the technical field of communication, which comprises: and a network detection module: the method is used for monitoring the state and performance parameters of the wireless network and collecting network data in real time; and a fault detection module: based on network monitoring data, an advanced fault detection algorithm is adopted to identify and locate faults in the wireless network, including weak signals, interference and transmission errors; a problem analysis module: analyzing and judging the detected faults, and determining the reasons and the influence scope of the faults; and an automatic processing module: and according to the result of the problem analysis, corresponding processing measures are automatically adopted to quickly repair faults or perform network optimization. And (3) automatic treatment: the system monitors and processes the problems in the wireless network in real time in an automatic mode, reduces manual intervention, improves the processing efficiency and accuracy, and has real-time performance: the system can monitor the network state and performance in real time, discover faults in time and take corresponding measures, so that the fault repairing time is greatly shortened.

Description

On-line diagnosis processing system for wireless network

Technical Field

The invention relates to the technical field of communication, in particular to a diagnosis processing system on a wireless network line.

Background

Communication is interpreted differently in different environments, and Communication (Communication) is interpreted singly after the occurrence of radio wave transmission Communication as the transmission of information, meaning the transmission and exchange of information from one place to another, the purpose of which is to transmit messages. However, communication is a continuous advancement of human civilization as the demand for messaging is increasing with the development of social productivity during human practice. Among various communication modes, a communication method for transmitting a message by using electricity is called Telecommunication (telecommunications), and the communication has the characteristics of rapidness, accuracy, reliability and the like, is hardly limited by time, place, space and distance, and is rapidly developed and widely applied; in the current process of mass exchange of ancient mankind, physical communication (postal communication) which combines cultural communication with continuous progress of physical economy is understood as an obstacle for restricting economic development by mankind.

The high-speed popularization and wide application of wireless networks make the demands of people on the performance of the wireless networks higher and higher. However, various problems and malfunctions in wireless networks often occur, which have a significant impact on the user's network usage experience. The current network diagnosis processing mode mainly depends on manual intervention, has high cost and is not accurate enough in real time, and therefore, the application provides a wireless network on-line diagnosis processing system.

Disclosure of Invention

The invention aims to provide a wireless network online diagnosis processing system which has the capability of automatically diagnosing and processing wireless network faults and improves network performance and user experience. The system can be widely applied to the field of wireless communication, and provides more reliable and efficient wireless network service for users, so that the problems of high-speed popularization and wide application of the wireless network in the background technology are solved, and the requirements of people on the performance of the wireless network are higher and higher. However, various problems and malfunctions in wireless networks often occur, which have a significant impact on the user's network usage experience. The current network diagnosis processing mode mainly depends on manual intervention, and has the problems of high cost and insufficient real-time accuracy.

In order to achieve the above purpose, the present invention provides the following technical solutions: a wireless network on-line diagnostic processing system comprising:

and a network detection module: the method is used for monitoring the state and performance parameters of the wireless network and collecting network data in real time;

and a fault detection module: based on network monitoring data, an advanced fault detection algorithm is adopted to identify and locate faults in the wireless network, including weak signals, interference and transmission errors;

A problem analysis module: analyzing and judging the detected faults, and determining the reasons and the influence scope of the faults;

and an automatic processing module: according to the result of the problem analysis, corresponding treatment measures are automatically adopted to quickly repair faults or perform network optimization;

and a user feedback module: real-time network status information, fault reports, and recommended solutions are provided to the user, enhancing user engagement and satisfaction.

As a further scheme of the invention: the network detection module further comprises the following sub-modules:

wireless signal strength monitoring: by measuring and recording the signal strengths at different locations, the system identifies signal coverage problems, such as areas or blind spots where signals are weak, and provides a corresponding solution;

signal interference detection: identifying and locating interference sources of adjacent frequency bands to the currently used frequency band by monitoring a wireless frequency spectrum, including other wireless devices or electromagnetic interference sources;

and (3) monitoring transmission quality: by continuously monitoring and analyzing the parameters, the system judges whether the network connection is stable, identifies transmission errors or congestion problems, and executes a corresponding network optimization strategy;

measurement of movement performance: by monitoring the switching process of the mobile device in the network, including switching delay and switching success rate, the system evaluates and optimizes roaming and switching strategies of the wireless network, providing smoother mobile experience;

Network capacity monitoring: by monitoring the load condition and the data flow of the access point in real time, the system judges the bottleneck and the congestion point of the network, and reminds a network manager to timely perform capacity expansion or optimization measures so as to ensure the network performance and the user experience.

As still further aspects of the invention: the fault detection module further comprises the following sub-modules:

and (3) detecting a link state: the system judges the stability and reliability of the link through real-time monitoring of the link connection quality, including the signal intensity, bit error rate and transmission rate parameters of the link;

protocol analysis: by monitoring and decoding the transmitted protocol messages, the system identifies whether protocol errors or illegal operations exist;

interference detection: by analyzing the frequency spectrum and the occupation condition of the wireless signals, the system identifies whether an interference source exists or not;

network topology analysis: by analyzing the network topology, including the connection relationship among the access point, the repeater and the mobile device, the system discovers whether a routing problem, topology error or loop exists;

abnormal behavior detection: by analyzing network flow and communication behaviors in real time, the system identifies and locates abnormal behaviors, adopts corresponding defensive measures, and ensures the safety and stability of the network.

As still further aspects of the invention: the problem analysis module further comprises the following sub-modules:

problem classification and priority assessment: by analyzing factors such as the type, severity, influence range and the like of the problems, the system classifies the problems into different categories and assigns corresponding priorities to each problem;

problem trace back and tracking: by establishing a problem tracing system, the system traces the origin and evolution process of the problem, wherein the problem tracing system comprises information such as a time stamp, related parameters, fault detection results and the like of the problem;

correlation analysis: by analyzing the association relation among the problems, including the space-time attribute, the common characteristics and the like of the problems, the system discovers the interaction and potential causal relation among the problems;

data mining and pattern recognition: the problem analysis module discovers potential problems or abnormal modes from a large amount of network monitoring data by utilizing data mining and pattern recognition technologies;

problem solution recommendation: and the problem analysis module recommends a corresponding problem solution according to the characteristics and the conclusion of the problem.

As still further aspects of the invention: the automatic processing module further comprises the following sub-modules:

automatic fault repair: the automatic processing module automatically executes a corresponding fault repairing strategy according to the type and severity of the fault detected by the diagnosis system;

Automatic optimization and adjustment: the automatic processing module automatically performs optimization adjustment of system parameters and configuration according to the result of problem analysis;

automatic flow control: the automatic processing module automatically controls and schedules the network traffic according to the network load and the performance index;

automatic safety protection: the automatic processing module automatically performs network security protection and risk management;

automatic reporting and notification: the automated processing module automatically generates a problem handling report and sends a related notification.

As still further aspects of the invention: the user feedback module further comprises the following sub-modules:

multichannel feedback reception: the user feedback module supports multiple channels to receive user feedback information;

intelligent problem analysis: the user feedback module rapidly and accurately analyzes the user feedback information through an intelligent algorithm and a natural language processing technology;

personalized interactions and guides: the user feedback module provides personalized interaction and guiding functions, helps a user to better describe the problem, and provides a solution;

user feedback tracking and feedback: the user feedback module tracks the processing process of the user feedback information and feeds back the progress situation to the user in real time;

User satisfaction evaluation: the user feedback module performs evaluation and analysis of user satisfaction.

Compared with the prior art, the invention has the beneficial effects that:

and (3) automatic treatment: the system monitors and processes the problems in the wireless network in real time in an automatic mode, reduces manual intervention, and improves the processing efficiency and accuracy.

Real-time performance: the system can monitor the network state and performance in real time, discover faults in time and take corresponding measures, so that the fault repairing time is greatly shortened.

Accurate positioning: through an advanced fault detection algorithm and a problem analysis module, the system can accurately locate and judge network faults and provide accurate fault reports and solutions.

User engagement: the system provides network status information and problem reports to the user and recommends solutions to enhance user engagement and satisfaction.

Network optimization: the system can realize the dynamic adjustment and optimization of the network through the optimization measure of the automatic processing module, and improve the network performance and user experience.

Drawings

FIG. 1 is a schematic diagram of a system architecture of an on-line diagnostic processing system for a wireless network according to the present invention;

FIG. 2 is a schematic diagram of a system architecture of a network detection module in a diagnostic processing system on a wireless network line according to the present invention;

FIG. 3 is a schematic diagram of a system architecture of a fault detection module in a diagnostic processing system on a wireless network line according to the present invention;

FIG. 4 is a schematic diagram of a system architecture of a problem analysis module in a wireless network on-line diagnostic processing system according to the present invention;

FIG. 5 is a schematic diagram of a system architecture of an automatic processing module in a diagnostic processing system on a wireless network line according to the present invention;

FIG. 6 is a schematic diagram of a system architecture of a user feedback module in a wireless network on-line diagnostic processing system according to the present invention.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

The terms first, second and the like in the description and in the claims, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged, as appropriate, such that embodiments of the present application may be implemented in sequences other than those illustrated or described herein, and that the objects identified by "first," "second," etc. are generally of a type and not limited to the number of objects, e.g., the first object may be one or more. Furthermore, in the description and claims, "and/or" means at least one of the connected objects, and the character "/", generally means that the associated object is an "or" relationship.

In the description of the present invention, it should be understood that the terms "center," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like indicate orientations or positional relationships based on the orientation or positional relationships shown in the drawings, merely to facilitate describing the present invention and simplify the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention.

In the description of the present invention, it should be noted that, unless explicitly stated and limited otherwise, the terms "mounted," "connected," and "disposed" are to be construed broadly, and may be fixedly connected, disposed, or detachably connected, disposed, or integrally connected, disposed, for example. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.

Referring to fig. 1 to 6, in an embodiment of the present invention, an on-line diagnosis processing system for a wireless network includes:

and a network monitoring module: the method is used for monitoring the state and performance parameters of the wireless network and collecting network data in real time.

And a fault detection module: based on network monitoring data, an advanced fault detection algorithm is adopted to identify and locate faults in the wireless network, including weak signals, interference, transmission errors and the like.

A problem analysis module: and analyzing and judging the detected faults, and determining the reasons and the influence scope of the faults.

And an automatic processing module: and according to the result of the problem analysis, corresponding processing measures are automatically adopted to quickly repair faults or perform network optimization, such as dynamically adjusting signal transmission power, frequency selection, routing paths and the like.

Preferably:

the network detection module is a key component of a diagnosis processing system on a wireless network line, and is responsible for monitoring the state and performance parameters of the wireless network and collecting network data in real time. The network detection module further comprises the following sub-modules:

wireless signal strength monitoring: the network detection module may monitor the strength of the wireless signal, i.e., a Received Signal Strength Indication (RSSI). By measuring and recording the signal strength at different locations, the system can identify signal coverage problems, such as areas of weak signals or blind spots, and provide corresponding solutions, such as adding additional radio base stations or optimizing radio signal coverage.

Signal interference detection: the network detection module may also detect interference conditions of the wireless signal. By monitoring the wireless spectrum, sources of interference adjacent to the currently used frequency band, including other wireless devices or electromagnetic interference sources, are identified and located. The system can provide corresponding processing schemes, such as adjusting frequency bands or taking interference elimination measures, according to the type and the position of the interference source.

And (3) monitoring transmission quality: the network detection module may monitor transmission quality parameters of the wireless network, such as transmission rate, packet loss rate, and delay. By continually monitoring and analyzing these parameters, the system can determine whether the network connection is stable, identify transmission errors or congestion problems, and implement corresponding network optimization strategies, such as adjusting modem parameters or optimizing network topology.

Measurement of movement performance: the network detection module may measure the mobility performance of the wireless network. By monitoring the handover process, including handover delay and handover success rate, of the mobile device in the network, the system can evaluate and optimize roaming and handover policies of the wireless network, providing a smoother mobile experience.

Network capacity monitoring: the network detection module may monitor capacity usage of the wireless network. By monitoring the load condition and the data flow of the access point in real time, the system can judge the bottleneck and the congestion point of the network, and remind a network manager to timely perform capacity expansion or optimization measures so as to ensure the network performance and the user experience.

Through the functions of the sub-module enriching network detection modules, the on-line diagnosis processing system of the wireless network can more comprehensively monitor and analyze various problems of the wireless network, thereby providing more accurate and real-time diagnosis and processing measures and optimizing network performance and user experience.

The fault detection module is an important component in a wireless network on-line diagnosis processing system. Based on network monitoring data, the method can identify and locate faults in the wireless network by adopting an advanced fault detection algorithm. The fault detection module further comprises the following sub-modules:

and (3) detecting a link state: the fault detection module may monitor the status of individual links in the wireless network. The system can judge the stability and reliability of the link through real-time monitoring of the link connection quality, including the parameters of the signal intensity, the bit error rate, the transmission rate and the like of the link. If the link is abnormal or interrupted, the system can give an alarm in time and take corresponding fault handling measures.

Protocol analysis: the fault detection module may perform in-depth analysis of the communication protocol in the wireless network. By monitoring and decoding the transmitted protocol messages, the system can identify whether there is a protocol error or a violation, such as an erroneous frame sequence, an erroneous MAC address, or an invalid data packet. The system can judge whether the fault is caused by a protocol problem or not and provide a targeted repair suggestion.

Interference detection: the fault detection module may detect an interference condition in the wireless network. By analyzing the spectrum and occupancy of the wireless signal, the system can identify whether an interference source, such as other wireless devices or electromagnetic interference sources, is present. The system may utilize the characteristics of the signal interference, match a predefined interference model, further locate the location of the interference source, and provide an interference cancellation scheme.

Network topology analysis: the fault detection module can perform network topology analysis and understand the structure and connection relation of the wireless network. By analyzing the network topology, including the connection relationships between access points, repeaters, mobile devices, the system can discover if there are routing problems, topology errors, loops, or the like. The system can utilize the topology analysis result to judge and correct the faults related to the network structure.

Abnormal behavior detection: the fault detection module may detect abnormal behavior in the wireless network, such as network traffic anomalies, illegal intrusions, or malicious attacks. By analyzing the network flow and the communication behavior in real time, the system can identify and locate the abnormal behavior, and adopts corresponding defensive measures to ensure the safety and stability of the network.

Through the functions of the sub-module enriching fault detection modules, the on-line diagnosis processing system for the wireless network can more accurately identify and position faults in the wireless network, timely take processing measures and improve fault diagnosis efficiency and network performance.

The problem analysis module is a key component in a diagnosis processing system on a wireless network line. The method and the system can deeply analyze the problems in the wireless network and provide a solution by using the collected network monitoring data and fault detection results and adopting an advanced problem analysis algorithm. The problem analysis module further comprises the following sub-modules:

problem classification and priority assessment: the problem analysis module may categorize and prioritize the problems detected by the diagnostic system. By analyzing factors such as the type, severity, and scope of impact of the problem, the system can categorize the problem into different categories and assign each problem a corresponding priority. This helps the network administrator to handle the problems in order, giving priority to solving the problems that have a greater impact on network performance and user experience.

Problem trace back and tracking: the problem analysis module may trace back and track the history of the problem. By establishing a problem tracing system, including information such as a time stamp, related parameters, fault detection results and the like of the problem, the system can trace the origin and evolution process of the problem. This helps to better understand the nature of the problem and provides historical data to support the problem's solution.

Correlation analysis: the problem analysis module may perform a problem correlation analysis. By analyzing the associations between the questions, including the spatiotemporal nature and common characteristics of the questions, etc., the system is able to discover interactions and potential causal relationships between the questions. This helps to quickly locate the root cause of the problem, providing a more accurate solution.

Data mining and pattern recognition: the problem analysis module may use data mining and pattern recognition techniques to discover potential problems or abnormal patterns from a large amount of network monitoring data. The system can automatically identify and extract data features and modes related to specific problems, and help network administrators to quickly discover problems and take corresponding treatment measures.

Problem solution recommendation: the problem analysis module may recommend corresponding problem solutions based on the characteristics and conclusions of the problem. By analyzing the processing and results of similar problems before, the system can provide a targeted solution or optimization strategy for the current problem. This helps to improve the efficiency and accuracy of problem handling.

Through the functions of the submodule enrichment problem analysis module, the wireless network online diagnosis processing system can further analyze and solve the problems in the wireless network, provide a more effective problem solution and further optimize network performance and user experience.

The automatic processing module is a component of a core in a wireless network on-line diagnosis processing system. Based on the results of fault detection and problem analysis, the method can automatically process and repair faults and problems in the wireless network by utilizing an automatic algorithm and strategy. The automatic processing module also comprises the following sub-modules:

automatic fault repair: the automatic processing module can automatically execute corresponding fault restoration strategies according to the types and the severity of faults detected by the diagnosis system. For example, for a problem of link outage, the system may automatically reconnect or switch to the backup link; for the problem of poor signal quality, the system may automatically adjust the signal booster or adjust the channel settings, etc. The automatic fault restoration can greatly reduce the need of manual intervention and improve the speed and accuracy of network restoration.

Automatic optimization and adjustment: the automatic processing module can automatically perform optimization adjustment of system parameters and configuration according to the problem analysis result. Through an automatic algorithm and mechanism, the system can automatically adjust the parameter setting of the wireless device, optimize the signal strength, the transmission rate and the like. For example, the system may automatically adjust configuration parameters of transmission power, channel selection, bandwidth allocation, etc., to provide more stable and efficient wireless network services.

Automatic flow control: the automatic processing module can automatically control and schedule the network traffic according to the network load and the performance index. The system can automatically identify and adjust bottlenecks in the network, and take corresponding flow control measures to optimize network bandwidth utilization and provide better user experience. For example, the system may automatically perform traffic limiting, load balancing, or priority adjustment to meet the needs of different applications and users.

Automatic safety protection: the automatic processing module can automatically perform network security protection and risk management. The system can automatically identify and prevent possible intrusion behavior, malicious attacks or network threats, and adopts corresponding security measures to protect the security of the wireless network. For example, the system can automatically trigger intrusion detection and firewall policies, automatically shield malicious IP addresses, or perform security policy updates, etc., to ensure the security of the network.

Automatic reporting and notification: the automated processing module may automatically generate a problem handling report and send a relevant notification. The system can automatically collect and analyze key information of the fault processing process, generate detailed diagnosis reports and help network administrators to know the processing condition and effect of the problems. Meanwhile, the system can automatically send notifications to related personnel, including information such as fault processing progress, solution suggestions or user influence, so as to ensure timely communication and feedback of the problems.

Through the functions of the automatic processing modules are enriched by the submodules, the on-line diagnosis processing system for the wireless network can realize automatic fault processing and problem solving, and greatly improve the efficiency of fault recovery and the stability of network performance.

The user feedback module is an important component in a wireless network on-line diagnosis processing system. The method is directly interacted with a user, receives feedback information of the user, and performs problem investigation and improvement according to feedback. The user feedback module further comprises the following sub-modules:

multichannel feedback reception: the user feedback module can support various channels to receive user feedback information. In addition to traditional text feedback, the system may also receive feedback information in the form of voice, pictures, or video. Thus, the feedback requirement of the user can be better met, and more comprehensive and accurate problem description is provided.

Intelligent problem analysis: the user feedback module can rapidly and accurately analyze the user feedback information through an intelligent algorithm and a natural language processing technology. The system can automatically identify and extract key information in the user feedback, such as problem type, time of occurrence, scope of influence, etc., and match with a library of known problems. This allows quick localization of the problem and preparation of the corresponding solution.

Personalized interactions and guides: the user feedback module may provide personalized interactive and guidance functions, help users better describe problems, and provide solutions. The system may prompt the user to provide more detailed information or to provide a related solution based on the user's feedback content. Therefore, the feedback quality of the user can be improved, the communication cost is reduced, and the solving process of the problem is accelerated.

User feedback tracking and feedback: the user feedback module can track the processing process of the user feedback information and feed back the progress situation to the user in real time. The system can automatically record the processing status of the feedback information and the feedback results of the processing personnel and notify the user of the latest progress regarding the problem resolution. Therefore, the interaction between the user and the system can be enhanced, the user satisfaction is improved, and a good user feedback closed loop is established.

User satisfaction evaluation: the user feedback module may perform evaluation and analysis of user satisfaction. The system can know the satisfaction degree and the demand change of the user through questionnaires, user ratings or emotion analysis and other modes. Therefore, the system can help to optimize the functions and performances of the system, improve the user experience and provide better service for the user.

Through the functions of the sub-module enriching user feedback module, the wireless network online diagnosis processing system can better interact with a user, understand the user demand, solve the problem in time and continuously improve the user satisfaction degree and the system performance.

In the present invention, network detection is achieved by a diagnostic processing system on a wireless network line. The following key steps and methods for implementing network detection are as follows:

data collection and monitoring: the system collects data of the network operation state in real time by monitoring the signal and data traffic in the wireless network. This may be achieved by a network listening device, a sensor or integrated with the network device. The system may collect various key metrics such as signal strength, transmission rate, network delay, packet loss rate, etc., for subsequent analysis and judgment.

Data preprocessing and analysis: the collected data is preprocessed and analyzed to identify possible faults and problems. Preprocessing includes operations such as data cleansing, feature extraction, etc., to ensure accuracy and availability of data. The analysis stage may use various algorithms and techniques such as statistical analysis, machine learning, data mining, etc., to extract fault features from the data, diagnose problems, optimize network configuration, etc.

Fault detection and problem diagnosis: the system detects possible faults and problems by analyzing the collected data. This may be done by modeling faults and problems and using supervised or unsupervised learning algorithms for fault detection and problem classification. The system can quickly locate the root cause of the problem according to the characteristics of the fault and the problem, and provide corresponding solutions and suggestions.

Real-time monitoring and alarming: the system can monitor the running state of the network in real time and alarm in real time according to preset thresholds and rules. When an abnormality occurs in the network or exceeds a set threshold, the system automatically triggers an alarm mechanism and notifies relevant personnel to process. Thus, network faults can be found and responded in time, and the influence of the faults on users is reduced.

Long term performance analysis and optimization: the system continuously collects, analyzes and records the operation data of the network for long-term performance analysis and optimization. Through trend analysis and anomaly detection of network performance, the system can be helped to find potential performance problems in time, and corresponding measures are adopted to optimize and improve. The system can automatically adjust network configuration parameters, improve network capacity, optimize resource allocation and the like so as to continuously improve network performance and user experience.

By the network detection method, the on-line diagnosis processing system of the wireless network can monitor, detect and diagnose network faults and problems in real time, help network administrators take measures in time to solve the problems, and ensure the stability and reliability of the network.

In the present invention, fault detection is achieved by a diagnostic processing system on a wireless network line. The following key steps and methods for implementing fault detection in the present invention are as follows:

data collection and monitoring: the system collects the data of the network operation state in real time by monitoring the information such as signals, data flow, equipment state and the like in the wireless network. This may be achieved by a network listening device, a sensor or integrated with the network device. The system can collect various key indexes such as signal strength, transmission rate, network delay, packet loss rate, equipment working state and the like.

Data preprocessing and analysis: the collected data is preprocessed and analyzed to identify possible faults. Preprocessing includes operations such as data cleansing, feature extraction, etc., to ensure accuracy and availability of data. The analysis stage may use various algorithms and techniques, such as statistical analysis, machine learning, data mining, etc., to identify features and rules of the fault from the data.

And (3) establishing a fault model: based on the existing data and knowledge, the system builds a fault model. The fault model may be a rule-based model or a machine learning-based model. The rule model identifies faults by matching and judging based on known fault patterns and rules. The machine learning model learns the pattern of failure by training a dataset and then classifies and predicts new data.

Fault detection and localization: the system uses the established fault model to perform fault detection and localization. Based on the collected data, the system can determine whether a fault exists according to the model, and locate the position and range of the fault as much as possible. The system can perform real-time fault detection and positioning according to the fault mode and the characteristics, and can process the fault through alarming or notifying related personnel.

Fault handling and solution: once a fault is detected, the system provides corresponding fault handling recommendations and solutions depending on the nature and severity of the fault. Solutions may include reconfiguring network devices, adjusting parameters, repairing connections or replacing failed devices, etc. The system can automatically or manually process the fault and verify and confirm after solving the fault.

Through the fault detection method, the on-line diagnosis processing system of the wireless network can monitor, detect and position faults in the network in real time, help network administrators to take measures to solve the faults in time, and ensure the stability and reliability of the network.

In the present invention, problem analysis is accomplished by a diagnostic processing system on a wireless network line. The following are key steps and methods for implementing problem analysis according to the present invention:

Data preprocessing and analysis: the collected data is preprocessed and analyzed to identify possible problems. Preprocessing includes operations such as data cleansing, feature extraction, etc., to ensure accuracy and availability of data. The analysis stage may analyze and discover potential problems from the data using various algorithms and techniques, such as statistical analysis, machine learning, data mining, and the like.

And (3) establishing a problem model: based on the existing data and knowledge, the system builds a problem model. The problem model may be a rule-based model or a machine learning-based model. The rule model identifies problems by matching and judging based on known problem patterns and rules. The machine learning model learns patterns of problems by training a dataset and then classifies and predicts new data.

Problem analysis and diagnosis: the system uses the established problem model for problem analysis and diagnosis. Based on the collected data, the system can determine whether a problem exists or not according to the model, and analyze and diagnose the cause and influence of the problem as much as possible. The system can conduct real-time problem analysis and diagnosis according to the problem modes and characteristics, and provide corresponding solutions and suggestions.

Problem solution and optimization: based on the results of the problem analysis, the system provides corresponding problem solutions and optimization suggestions. Solutions may include reconfiguring network devices, adjusting parameters, optimizing resource allocation, repairing connections or replacing failed devices, and the like. The optimization suggestions may relate to network cabling, signal enhancement, equipment upgrades, etc. to improve overall network performance and user experience.

Through the problem analysis method, the wireless network online diagnosis processing system can collect, analyze and diagnose the problems in the network in real time, help a network manager determine the cause and the solution of the problems, and perform network optimization and improvement. This helps to improve the stability, reliability and performance of the network, meeting the needs of the user.

In the present invention, the automated processing module is designed to quickly and efficiently process faults or problems detected by the diagnostic system. The following is a specific processing method of the automatic processing module in the invention:

fault/problem identification: the automatic processing module firstly rapidly and accurately identifies the type and the nature of the fault or the problem through methods such as rule matching, machine learning and the like according to fault/problem information provided by the diagnosis system.

The automatic processing flow comprises the following steps: according to the identified fault/problem type, the automatic processing module automatically performs corresponding processing operation according to a preset processing flow or rule.

The processing operation comprises the following steps: the automated processing module may perform a series of processing operations, such as reconfiguring network devices, restarting devices, adjusting parameters, repairing connections, issuing alarm notifications, etc., as the case may be.

Abnormal data processing: the automatic processing module can also process the abnormal data. When abnormal data is detected, errors can be corrected, data loss repaired, network connection restored, etc. by analyzing and processing the data.

Status monitoring and verification: the automatic processing module continuously monitors the state and change of faults or problems in the processing process and timely provides feedback. Meanwhile, the automatic processing module can also verify the result of the processing operation, so that the fault resolution and the network recovery are ensured.

Recording and feedback: the automated processing module will record the process and results of each fault/problem for subsequent reference and analysis. Meanwhile, the system can also provide feedback of processing results to a network administrator or related personnel, including faults which are successfully resolved, problems which are not resolved, reasons for processing failure, and the like.

By the specific processing method of the automatic processing module, the on-line diagnosis processing system of the wireless network can rapidly and accurately perform automatic processing of faults/problems, reduce manual intervention and response time, and improve the reliability and stability of the network.

In the present invention, a user feedback module is included in addition to the automatic processing module. The user feedback module is used for collecting and processing feedback information of the user so as to improve system performance and user experience. The following is a specific processing method of the user feedback module in the present invention:

Feedback collection: the user feedback module collects feedback information of the user through various channels, such as an in-application feedback form, an email, an online forum and the like. The user may report network problems, error information, unsatisfactory user experience, etc.

Feedback classification and arrangement: the collected feedback information is classified and sorted, and similar feedback is grouped together for analysis and processing. This may be accomplished using techniques such as text classification, natural language processing, and the like.

Abnormality detection and screening: in processing the feedback information, the user feedback module may use anomaly detection techniques to screen and identify potential problems. For example, by identifying abnormal feedback or problem patterns that occur more frequently, the system can determine whether a systematic fault or defect exists.

Problem analysis and prioritization: the user feedback module analyzes the collected feedback information to determine the severity, priority and influence range of each problem. This may help the system development team determine the problems and improvement points that need to be addressed in priority.

Problem recovery and resolution: the user feedback module can timely reply to the feedback of the user, and inform the user of receiving the feedback and representing thank you. For the problem that has been solved, the module will inform the user that the problem has been treated and solved. For problems that cannot be resolved immediately, the module will explain the cause and keep in communication.

Data analysis and improvement: the user feedback module performs statistics and analysis on the collected feedback information, finds common problems and bottlenecks in the system, and feeds the information back to the development team. The development team can improve and optimize the system according to the information fed back by the user to provide a better user experience.

By the processing method of the user feedback module, the on-line diagnosis processing system of the wireless network can timely acquire feedback information of the user, quickly identify and solve problems, and improve system performance and user satisfaction. Meanwhile, through information analysis fed back by a user, the system can be continuously optimized and improved, and the stability and reliability of the system are continuously improved.

Embodiments of the invention may include the steps of:

system deployment and installation: in a wireless network environment, it is first necessary to deploy and install the wireless network on-line diagnostic processing system of the present invention. This involves properly installing the software and hardware components of the system on the network management center or server and ensuring proper connection to the network devices.

System configuration and initialization: the system configuration and initialization is carried out, including setting basic parameters of the system, connecting network equipment and rules and flows of network detection, fault diagnosis and automatic processing related to configuration. This may be accomplished through a management interface of the system while ensuring that the system communicates properly with the associated devices.

Network device monitoring and diagnostics: the system begins monitoring and diagnosing network devices. The method can collect and analyze data of the network equipment periodically or in real time, and check the state, performance and connection condition of the equipment. Once a problem is found, the system generates a fault report and triggers a corresponding automated process flow.

Automatic processing operation: when the system detects a fault or a problem, the automatic processing module automatically performs related processing operations according to a preset processing flow. For example, if a network device connection interruption is detected, the automated processing module may attempt to reconfigure the device, restart the device, or repair the connection to resume normal operation of the network as soon as possible.

User feedback collection and processing: the user feedback module of the system begins to collect and process feedback information of the user. The user may report problems or provide feedback to the system through a system interface or other channel. The system will collect, sort and sort the feedback information and combine with the results of the automated processing module to help identify and solve the problem.

Problem solving and performance optimization: according to the processing result of the automatic processing module and the feedback information of the user feedback module, a development team of the system can identify the problem and carry out corresponding solving measures. This may include adjusting system parameters, repairing software bugs, increasing network capacity, etc. At the same time, system development teams can also utilize this information to optimize the performance and stability of the system.

Operation and continuous improvement: once the system is put into service, continuous maintenance and improvement work is required. This includes monitoring and maintaining the system, periodically updating system software and rules, collecting and analyzing operational data, discovering problems, and improving the performance and user experience of the system.

Through the embodiment, the on-line diagnosis processing system of the wireless network can help network management personnel to quickly identify and solve network faults or problems, and improve the stability and reliability of the network. Meanwhile, the user feedback module can also collect feedback information of the user and help the system to continuously optimize and improve.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element. Furthermore, it should be noted that the scope of the methods and apparatus in the embodiments of the present application is not limited to performing the functions in the order shown or discussed, but may also include performing the functions in a substantially simultaneous manner or in an opposite order depending on the functions involved, e.g., the described methods may be performed in an order different from that described, and various steps may also be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

The embodiments of the present application have been described above with reference to the accompanying drawings, but the present application is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many forms may be made by those of ordinary skill in the art without departing from the spirit of the present application and the scope of the claims, which are also within the protection of the present application.

Claims

1. The wireless network on-line diagnosis processing system is characterized in that: comprising the following steps:

2. The wireless network on-line diagnostic processing system of claim 1, wherein: the network detection module further comprises the following sub-modules:

3. The wireless network on-line diagnostic processing system of claim 1, wherein: the fault detection module further comprises the following sub-modules:

4. The wireless network on-line diagnostic processing system of claim 1, wherein: the problem analysis module further comprises the following sub-modules:

5. The wireless network on-line diagnostic processing system of claim 1, wherein: the automatic processing module further comprises the following sub-modules:

6. The wireless network on-line diagnostic processing system of claim 1, wherein: the user feedback module further comprises the following sub-modules: