Fault Type Determination via Real-Time Feature Calculation
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Solution Overview
Problem
Current methods for determining fault types in telecommunication networks are inefficient and inaccurate, relying heavily on manual intervention and customer service representative experience, which leads to slow processing and high manual costs.
Innovation Solution
A method and apparatus that perform online real-time calculation of operating data to generate feature values, using a fault classification model trained on known fault types to quickly and accurately determine fault types by matching operating feature values with the fault classification model, reducing manual intervention and improving processing speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual analysis of error codes by customer service representatives is used, then fault type determination can be performed, but processing efficiency is low and manual costs are high
Solution Approach 1:
The system enables self-service by automatically analyzing error codes and determining fault types without human intervention. The fault determination system autonomously processes error reporting logs and signaling data to identify fault types, eliminating the need for customer service representatives to manually analyze error codes while improving processing efficiency and reducing manual costs
Solution Approach 2:
The patent replaces the mechanical manual analysis process with an automated electronic system. Instead of customer service representatives manually examining error codes and signaling data, the system uses automated algorithms to analyze error reporting logs and signaling data, extract error codes, and determine fault types, thereby substituting human mechanical work with automated computational processes
2Productivity
If separate analysis of error codes in signaling data and error reporting logs is performed, then fault type can be determined, but determination efficiency is not high
Solution Approach 1:
The system merges the separate analysis processes for signaling data and error reporting logs into a unified fault determination workflow. The fault determination system simultaneously processes both data sources, extracts error codes from each, and integrates the analysis results to determine fault types, thereby improving determination efficiency by eliminating redundant separate analysis steps while managing complexity through integrated processing
3Measurement precision
If customer service representatives determine fault types based on experience, then fault determination can be made, but accuracy cannot be stably ensured due to experience limitations
Solution Approach 1:
The system replaces experience-based manual judgment with automated algorithmic analysis that consistently processes error codes from signaling data and error reporting logs. The fault determination system autonomously identifies fault types based on objective data analysis rather than subjective human experience, ensuring stable and reproducible accuracy across all fault determinations without variability due to individual representative expertise
Solution Approach 2:
The system implements feedback mechanisms by analyzing actual error codes from network operations and using this information to determine fault types. The fault determination process continuously receives feedback from error reporting logs and signaling data, allowing the system to accurately identify and classify faults based on real-world network conditions and error patterns rather than relying on predetermined experience-based rules
Data Source
AI summary
This application discloses a method and an apparatus for determining a fault type. The method includes: performing online real-time calculation on operating data generated by each of a plurality of users within a preset period, to obtain an operating feature value corresponding to the operating data generated by each of the plurality of users within the preset period; receiving a fault classification request, where the fault classification request requests to determine a fault type of a fault that is caused for a target user before a target moment; and determining, according to the fault classification request, the fault type of the fault that is caused for the target user before the target moment based on a fault classification model and an operating feature value that is of the target user within at least one preset period.