Intelligent judgment method and system for network wiring

Abstract

The invention discloses a network wiring intelligent judgment method and system, which comprises data acquisition and preprocessing, fault judgment and processing, visual interface and remote access, the data acquisition and preprocessing comprises real-time detection and judgment, anomaly detection and fault positioning, and the fault judgment and processing comprises automatic repair suggestion and learning optimization. According to the network wiring intelligent judgment method and system, the working efficiency is improved, the automatic diagnosis system can greatly improve the diagnosis speed and accuracy of network wiring faults, and the maintenance cost is reduced; downtime is reduced, fault points are quickly positioned, network downtime can be shortened, and the risk of service interruption is reduced; the system is widely applicable to various network environments, guarantees the safety and reliability of a network wiring system and the intelligent and automatic functions of the system, simplifies the operation and management process of a user, improves the working efficiency and experience of the user, and reduces the maintenance cost and risk.

Description

Technical Field

[0001] The present invention relates to the technical field of network wiring, and in particular to a network wiring intelligent judgment method and system. Background Art

[0002] Network wiring is an important part of the modern information society, and its good condition is crucial for data transmission and communication. However, due to the complexity of the network and the difficulty of maintenance, the diagnosis and troubleshooting of network wiring faults usually requires a lot of manpower and time costs.

[0003] Therefore, it is crucial to develop an intelligent network wiring diagnostic method to improve diagnostic efficiency and accuracy and reduce maintenance costs. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the present invention provides a network wiring intelligent judgment method and system, which aims to solve the problems of low diagnostic efficiency and accuracy, high maintenance cost, etc.

[0005] In order to achieve the above-mentioned purpose of the invention, the technical solution adopted by the present invention is: a network wiring intelligent judgment method and system, including data collection and preprocessing, fault judgment and processing, visual interface and remote access, the data collection and preprocessing contain real-time detection and judgment, anomaly detection and fault location, the fault judgment and processing includes automatic repair suggestions and learning optimization.

[0006] Furthermore, the basis for the normal operation of the data collection system includes step 1: connectivity data, collecting information such as connection status, connection speed, network delay, etc. between network devices;

[0007] Step 2: Traffic data, the amount of data transmitted in the network and the traffic pattern;

[0008] Step 3: Physical layer data, cable interface status, signal strength, voltage, etc.

[0009] Step 4: Device logs. Network devices usually record runtime events and error logs.

[0010] Step 5: Network topology data, including the location, connection relationship and topology of each device in the network;

[0011] Comprehensive analysis of the above data and preprocessing, including data cleaning and feature extraction, can fully understand the operating status of the network.

[0012] Furthermore, the real-time detection and judgment includes monitoring of power parameters, observation of voltage, current, frequency and power factor, and temperature monitoring, which are used to reflect the working status and operating status of the equipment, and data communication status monitoring, mainly network connection status, communication rate and data transmission quality, to ensure the timeliness and accuracy of monitoring data, and to judge in real time whether there are any abnormal conditions in the network wiring, such as signal attenuation, transmission failure, etc., by continuously monitoring the status of the network wiring and based on the pre-trained model.

[0013] Furthermore, the anomaly detection and fault location include the system detecting and locating the real-time detection parts by comparing the network wiring data with the normal mode, mainly locating the abnormal points and monitoring the short circuit, open circuit, grounding fault, etc. in the network wiring. The system can detect and locate the fault point through changes in parameters such as current and voltage, and can quickly discover abnormal situations and locate possible fault points, such as broken wires, loose wires, etc.

[0014] Furthermore, the automatic repair suggestions include fault type identification and location, fault cause analysis, analysis of the causes of the fault, such as equipment aging, overload, external damage, etc., in order to formulate corresponding repair strategies, and provide specific repair suggestions based on the fault type and location, including replacing damaged equipment, repairing lines, and increasing load balancing, and providing measures to prevent faults, such as regular equipment inspections, enhanced maintenance, and reasonable load planning, etc., to reduce the occurrence of faults.

[0015] Furthermore, the learning optimization includes mining and analyzing historical data based on big data technology and data analysis, discovering potential rules and patterns, providing data support and guidance for system optimization, tuning and optimizing model parameters, and using automated methods to search for optimal parameter combinations, thereby improving system performance and generalization capabilities, improving diagnostic accuracy and efficiency, and adapting to different network environments and fault types.

[0016] Furthermore, the visualization interface and remote access include an intuitive user interface that enables remote access and management, making it convenient for maintenance personnel to monitor network status in real time.

[0017] The beneficial effects of the present invention are:

[0018] The network wiring intelligent judgment method and system of the present invention improve work efficiency. The automated diagnosis system can greatly improve the diagnosis speed and accuracy of network wiring faults and reduce maintenance costs. It reduces downtime and quickly locates fault points, which can shorten network downtime and reduce the risk of business interruption. It is widely applicable to various network environments, including enterprise networks, data centers, smart homes, etc., and has broad application prospects. The system can monitor safety hazards and abnormal situations, provide safety warnings and suggestions, help users strengthen safety management and control, and ensure the safety and reliability of network wiring systems. The intelligent and automated functions of the system simplify the user's operation and management processes, improve the user's work efficiency and experience, and reduce maintenance costs and risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 The present invention is a schematic diagram of a network wiring intelligent judgment method and system structure. DETAILED DESCRIPTION

[0020] The specific implementation of the present invention is further described below in conjunction with the accompanying drawings, wherein the same components are represented by the same reference numerals.

[0021] It should be noted that the words "front", "rear", "left", "right", "up" and "down" used in the following description refer to directions in the drawings, and the words "inside" and "outside" refer to directions toward or away from the geometric center of a specific component, respectively.

[0022] In order to make the contents of the present invention more clearly understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0023] like Figure 1 As shown, a network wiring intelligent judgment method and system include data collection and preprocessing, fault judgment and processing, visual interface and remote access. Data collection and preprocessing include real-time detection and judgment, anomaly detection and fault location. Fault judgment and processing include automatic repair suggestions and learning optimization.

[0024] The basis for the normal operation of the data collection system includes step 1: connectivity data, collecting information such as the connection status, connection speed, network delay, etc. between network devices;

[0025] Step 2: Traffic data, the amount of data transmitted in the network and the traffic pattern;

[0026] Step 3: Physical layer data, cable interface status, signal strength, voltage, etc.

[0027] Step 4: Device logs. Network devices usually record runtime events and error logs.

[0028] Step 5: Network topology data, including the location, connection relationship and topology of each device in the network;

[0029] Comprehensive analysis of the above data and preprocessing, including data cleaning and feature extraction, can fully understand the operating status of the network.

[0030] Through the above solution, traffic data can analyze network usage, identify abnormal traffic patterns and bottlenecks, and thus guide network optimization and fault diagnosis. Physical layer data can detect cable breakage, looseness or other physical failures, so as to diagnose and repair them in a timely manner. Device logs can analyze warnings and error messages to promptly detect device failures or abnormal conditions. Network topology data can be used to locate faults and analyze paths.

[0031] Real-time detection and judgment include power parameter monitoring, voltage, current, frequency and power factor observation, temperature monitoring, which are used to reflect the working status and operating status of the equipment, data communication status monitoring, mainly network connection status, communication rate and data transmission quality, to ensure the timeliness and accuracy of monitoring data, by continuously monitoring the status of network wiring and based on pre-trained models, to judge in real time whether there are any abnormal conditions in the network wiring, such as signal attenuation, transmission failure, etc.

[0032] Through the above scheme, power parameter monitoring can reflect the working status and load conditions of network wiring, which helps to detect abnormal conditions in time. Data communication status monitoring ensures the normal operation of data communication equipment, guarantees the timeliness and accuracy of monitoring data, and improves the safety, stability and reliability of network wiring.

[0033] Anomaly detection and fault location include the system detecting and locating the real-time detection parts by comparing the network wiring data with the normal mode, mainly locating the abnormal points and monitoring the short circuit, open circuit, grounding fault, etc. in the network wiring. The system can detect and locate the fault point through changes in parameters such as current and voltage. It can quickly discover abnormal situations and locate possible fault points, such as broken wires, loose wires, etc.

[0034] Automatic repair suggestions include fault type identification and location, fault cause analysis, and analysis of the causes of the fault, such as equipment aging, overload, external damage, etc., in order to formulate corresponding repair strategies. According to the type and location of the fault, specific repair suggestions are provided, including replacing damaged equipment, repairing lines, and increasing load balancing. Measures to prevent faults are provided, such as regular equipment inspections, enhanced maintenance, and reasonable load planning, etc., to reduce the occurrence of faults.

[0035] Through the above solution, the system can automatically repair or adjust some simple faults, reducing manual intervention.

[0036] Learning optimization includes mining and analyzing historical data based on big data technology and data analysis, discovering potential rules and patterns, providing data support and guidance for system optimization, tuning and optimizing model parameters, and using automated methods to search for the optimal parameter combination, thereby improving system performance and generalization capabilities, improving diagnostic accuracy and efficiency, and adapting to different network environments and fault types.

[0037] Through the above scheme, the accuracy and efficiency of fault diagnosis are improved by learning and training historical data.

[0038] Visualization interface and remote access include an intuitive user interface that can be accessed and managed remotely, allowing maintenance personnel to monitor network status in real time.

[0039] The working principle of the patent of this invention is to collect network wiring data: the system collects network wiring data in real time through sensors and network equipment. Data processing and analysis: process and analyze the collected data, extract features and make classification judgments. Abnormal detection and processing: identify possible abnormal situations, issue alarms, and automatically take corresponding processing measures. Status optimization and adjustment: automatically optimize the layout and configuration of network wiring according to real-time network status and needs. Remote monitoring and management: users can remotely monitor and manage the system through the network, understand the status and performance of network wiring in real time, and make necessary adjustments and maintenance.

[0040] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention shall be included in the protection scope of the present invention.

Claims

1. A network wiring intelligent judgment method and system, including data collection and preprocessing, fault judgment and processing, visual interface and remote access, characterized in that: The data collection and preprocessing include real-time detection and judgment, anomaly detection and fault location, and the fault judgment and processing include automatic repair suggestions and learning optimization.

2. A network wiring intelligent judgment method and system according to claim 1, characterized in that: The basis for the normal operation of the data collection system includes step 1: connectivity data, collecting information such as connection status, connection speed, network delay, etc. between network devices; Step 2: Traffic data, the amount of data transmitted in the network and the traffic pattern; Step 3: Physical layer data, cable interface status, signal strength, voltage, etc. Step 4: Device logs. Network devices usually record runtime events and error logs. Step 5: Network topology data, including the location, connection relationship and topology of each device in the network; Comprehensive analysis of the above data and preprocessing, including data cleaning and feature extraction, can fully understand the operating status of the network.

3. A network wiring intelligent judgment method and system according to claim 1, characterized in that: The real-time detection and judgment includes monitoring of power parameters, observation of voltage, current, frequency and power factor, and temperature monitoring, which are used to reflect the working status and operating status of the equipment, and data communication status monitoring, mainly network connection status, communication rate and data transmission quality, to ensure the timeliness and accuracy of monitoring data, and to judge in real time whether there are any abnormal conditions in the network wiring, such as signal attenuation, transmission failure, etc., by continuously monitoring the status of the network wiring and based on the pre-trained model.

4. A network wiring intelligent judgment method and system according to claim 1, characterized in that: The abnormality detection and fault location include the system detecting and locating the real-time detection parts by comparing the network wiring data with the normal mode, mainly locating the abnormal points and monitoring the short circuit, open circuit, grounding fault, etc. in the network wiring. The system can detect and locate the fault point through the changes of current, voltage and other parameters, and can quickly discover abnormal situations and locate possible fault points, such as broken wires, loose wires, etc.

5. A network wiring intelligent judgment method and system according to claim 1, characterized in that: The automatic repair suggestions include fault type identification and location, fault cause analysis, and analysis of the causes of the fault, such as equipment aging, overload, external damage, etc., so as to formulate corresponding repair strategies. According to the fault type and location, specific repair suggestions are provided, including replacing damaged equipment, repairing lines, and increasing load balancing. Measures to prevent faults are provided, such as regular equipment inspections, enhanced maintenance, and reasonable load planning, so as to reduce the occurrence of faults.

6. A network wiring intelligent judgment method and system according to claim 1, characterized in that: The learning optimization includes mining and analyzing historical data based on big data technology and data analysis, discovering potential rules and patterns, providing data support and guidance for system optimization, tuning and optimizing model parameters, and using automated methods to search for the optimal parameter combination, thereby improving system performance and generalization capabilities, improving diagnostic accuracy and efficiency, and adapting to different network environments and fault types.

7. A network wiring intelligent judgment method and system according to claim 1, characterized in that: The visualization interface and remote access include an intuitive user interface that enables remote access and management, making it convenient for maintenance personnel to monitor network status in real time.

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