Weighted Average Distributed Reflectometry for Network Fault Detection
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Solution Overview
Problem
Conventional distributed reflectometry methods face interference issues from other reflectometers in wired networks, leading to residual noise and ambiguity in fault detection, especially in complex network structures like Y networks.
Innovation Solution
A weighted average distributed reflectometry device and method that uses specific weighting coefficients to cancel out interference from other reflectometers, allowing for improved signal-to-noise ratio and accurate fault detection by orthogonal or synchronized weighting vectors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple reflectometers are used simultaneously in distributed reflectometry, then network diagnosis coverage is improved, but interference noise from other reflectometers increases
Solution Approach 1:
The patent converts the harmful interference from other reflectometers into a beneficial signal by using correlation processing. Each reflectometer transmits a known test signal sequence, and the receiving reflectometer correlates the received signal with the expected sequence. This correlation process extracts the desired signal while suppressing uncorrelated interference noise from other reflectometers, effectively transforming the harmful multi-reflectometer environment into a useful diagnostic tool.
Solution Approach 2:
The patent introduces correlation processing as an intermediary mechanism between signal transmission and fault detection. The correlation operation acts as a mediator that separates the desired reflected signal from the interfering signals of other reflectometers. By using the known test signal sequence as a reference, the correlation process selectively passes through the matching signal components while filtering out mismatched interference, enabling simultaneous operation of multiple reflectometers.
2Measurement precision
If conventional signal averaging is used to improve signal-to-noise ratio, then measurement precision is improved, but residual interference noise remains
Solution Approach 1:
The patent transforms the interference problem into a solution by using correlation processing instead of simple averaging. While conventional averaging reduces random noise, it cannot eliminate systematic interference from other reflectometers. The correlation method converts the harmful correlated interference into a detectable signal component that can be separated from uncorrelated noise, achieving superior noise rejection and enabling precise fault detection even in the presence of multiple active reflectometers.
3Measurement precision
If test signals are transmitted periodically for averaging, then signal-to-noise ratio is improved, but ambiguity in fault location increases in complex networks
Solution Approach 1:
The patent applies segmentation by assigning unique test signal sequences to each reflectometer in the network. Instead of using identical periodic signals that cause ambiguity, each reflectometer transmits a distinct sequence (e.g., different phases, frequencies, or code patterns). The correlation processing at each reflectometer can then identify which transmitted sequence produced which reflected signal, enabling precise determination of fault location and eliminating ambiguity in complex network topologies while maintaining the benefits of periodic transmission for averaging.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method effectively cancels out interference noise, enabling precise fault detection and network topology analysis without residual noise, even in complex network structures, and allows for the use of various test signals like multicarrier signals.
Implementation Method 1
Reflectometry consists in transmitting a signal over a cable network and in then measuring the returned signals. The delay and amplitude of these echoes enable information to be obtained about the structure or electrical faults present in said network.
Data Source
AI summary
A distributed reflectometry device for diagnosing a network is disclosed. According to one aspect, the device includes at least one transmission line and several reflectometers connected to the network. A transmission portion of the device includes a first memory configured to store at least one test signal and a second memory configured to store weighting coefficients. The transmission portion may also include a first multiplier of a test signal (s) with a coefficient βm, for producing a measurement m and a digital-to-analog converter connected to the line. A reception portion of the device includes an analog-to-digital converter configured to receive a signal from the line and provide a vector for the measurement m, a second multiplier of configured to multiply the vector with the coefficient βm, an averaging module, and a post-processing and analysis module.