Telecommunication Fault Detection Using Retraining Event Data Analysis
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Solution Overview
Problem
Identifying and addressing anomalies or defects in telecommunication systems, such as DSL networks, can be challenging due to their intermittent nature, leading to costly and time-consuming maintenance efforts, and often results in unnecessary hardware replacements.
Innovation Solution
A method that collects retrain event data from ports at a target site, filters and categorizes it, and applies screening criteria with evaluation metrics to identify fault conditions, allowing for targeted remedial actions like hardware replacement or software updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If maintenance personnel travel to distribution points to identify fault sources using test equipment, then fault identification accuracy is improved, but maintenance cost and time consumption increase
Solution Approach 1:
The patent replaces the mechanical approach of maintenance personnel physically traveling to distribution points with an automated electronic system that collects and analyzes retrain event data remotely. The fault detection device automatically gathers retrain data from multiple ports and applies screening criteria to identify fault conditions, eliminating the need for manual on-site testing while maintaining high diagnostic accuracy.
Solution Approach 2:
The system enables self-diagnosis by automatically collecting retrain event data, processing it through filtering and categorization, and identifying fault conditions without requiring maintenance personnel intervention. The automated fault detection device performs the entire diagnostic process independently, from data collection to fault identification, significantly reducing maintenance time and costs.
2Reliability
If hardware components are replaced based on frequent retrain sequences, then service reliability is improved, but hardware waste increases due to unnecessary replacements
Solution Approach 1:
The patent applies local quality by providing differentiated diagnostic results for specific ports rather than blanket replacement of all hardware components. The system analyzes retrain event data port-by-port, applying screening criteria to identify which specific ports have fault conditions. This localized approach ensures that only the affected ports or components are replaced, preventing unnecessary hardware waste while maintaining service reliability.
Solution Approach 2:
The automated fault detection system replaces the mechanical approach of replacing hardware based on simple retrain frequency thresholds with an intelligent diagnostic system. The system collects detailed retrain event data, filters and categorizes it, and applies comprehensive screening criteria to distinguish between transient issues and actual hardware faults. This substitution prevents premature or unnecessary hardware replacements while ensuring reliable service through accurate fault identification.
3Measurement precision
If retrain event data is collected and analyzed from all ports, then fault detection accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the retrain event data processing into distinct stages: data collection, filtering to remove irrelevant events, categorization into meaningful groups, and finally analysis against screening criteria. This segmented approach breaks down the complex task of analyzing data from all ports into manageable steps, reducing processing complexity while maintaining high fault detection accuracy through systematic analysis.
Solution Approach 2:
The system extracts only the relevant information from collected retrain event data by applying filtering criteria to remove noise and irrelevant events. The filtering step extracts meaningful patterns from the raw data, keeping only the events that are indicative of actual fault conditions. This extraction process simplifies the subsequent analysis by focusing on critical data points rather than processing all raw events, thereby reducing complexity while preserving detection accuracy.
Data Source
AI summary
Systems and methods are provided for detecting fault conditions associated with an distribution point in a communication system using retrain event data. The retrain event data is collected for all of the ports associated with a target site of the distribution point. The collected retrain event data can then be organized into several different categories such as upstream related retrain events and downstream related retrain events. A screening criteria can be selected that is associated with a fault condition. The screening criteria can be evaluated using one or more evaluation metrics. Each evaluation metric can be based on normalized parameters generated from the categorized retrain event data. If all of the evaluation metrics associated with a screening criteria are satisfied, then the screening criteria is satisfied and the target site is determined to have a fault condition.