Fiber Intrusion Detection with Wind-Rejecting Adaptive Thresholds

Solution Overview

Problem

Existing optical fiber intrusion detection systems struggle to differentiate between intrusion events and environmental noise, particularly in the presence of strong weather conditions like wind and rain, leading to false alarms and reduced responsiveness.

Innovation Solution

A method involving a transform function to convert optical signals into frequency-dependent coefficients, comparing them against an envelope of coefficients, and adjusting sensitivity by increasing or decreasing envelope values based on environmental noise conditions, using a FIFO buffer to delay desensitization and a floor value to prevent false alarms.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If the system increases sensitivity to detect intrusion events, then detection accuracy improves, but false alarms increase due to environmental noise like wind

Engineering Contradiction:

Improvedetection accuracyVSAvoidfalse alarm rate

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

The system dynamically adjusts the sensitivity threshold based on environmental conditions. The threshold is not fixed but adapts in real-time to differentiate between normal environmental noise and actual intrusion events, resolving the contradiction between maintaining high detection accuracy while minimizing false alarms

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes the sensitivity parameter dynamically based on measured environmental noise levels. By monitoring the noise floor and adjusting the detection threshold accordingly, the system maintains optimal detection accuracy across varying environmental conditions without triggering false alarms

Inventive Principle:

Principle #35Parameter changes

2Reliability

If the system decreases sensitivity to reduce false alarms, then reliability improves, but detection accuracy decreases and intrusions may be missed

Engineering Contradiction:

Improvefalse alarm rateVSAvoiddetection accuracy

Core Design Contradiction:

ReliabilityVSMeasurement precision

Solution Approach 1:

The system dynamically adjusts the sensitivity threshold based on environmental conditions. The threshold is not fixed but adapts in real-time to differentiate between normal environmental noise and actual intrusion events, resolving the contradiction between maintaining high detection accuracy while minimizing false alarms

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system uses feedback from continuous environmental monitoring to adjust detection parameters. By analyzing the noise floor and intrusion patterns over time, the system learns to distinguish between benign environmental variations and genuine threats, maintaining both reliability and detection accuracy

Inventive Principle:

Principle #23Feedback

3Device complexity

If the system uses fixed sensitivity threshold, then device complexity is low, but adaptability to environmental conditions deteriorates

Engineering Contradiction:

Improvealgorithm complexityVSAvoidenvironmental adaptability

Core Design Contradiction:

Device complexityVSAdaptability or versatility

Solution Approach 1:

The system performs self-adjustment by automatically monitoring environmental noise levels and adapting its detection threshold without external intervention. This self-service capability enables the system to maintain optimal performance across diverse environmental conditions while keeping the control mechanism relatively simple

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system uses feedback from continuous environmental monitoring to adjust detection parameters. By analyzing the noise floor and intrusion patterns over time, the system learns to distinguish between benign environmental variations and genuine threats, maintaining both reliability and detection accuracy

Inventive Principle:

Principle #23Feedback

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 system effectively distinguishes intrusion events from environmental noise, maintaining high detection accuracy during weather conditions by dynamically adjusting sensitivity, reducing false alarms, and ensuring timely response to actual intrusions.

Implementation Method 1

Distributed Acoustic Sensing (DAS) where vibrations and displacements cause localized shifts in the path length of the optical fiber

Methodology Applied

Scientific EffectDistributed Acoustic Sensing (DAS):

Implementation Method 2

This is detected by a high precision optical Time Domain Reflectometer (OTDR)

Methodology Applied

Scientific EffectTime Domain Reflectometer (OTDR):

Implementation Method 3

using a transform function to convert the sequence of digital samples into a set of frequency dependent transform coefficients

Methodology Applied

Scientific EffectFourier Transform:

Data Source

PatentUS12517274B2Intrusion detection algorithm with wind rejection heuristic

Publication Date: 2026.01.06 NETWORK INTEGRITY SYSTEMS INC

AI summary

A method is provided for analyzing a monitoring signal from a sensing system to determine an alarm condition, where the monitoring signal is provided as a stream of digital values which are analyzed using a frequency-based transform to generate a set of transform coefficients which are compared to a set of envelope coefficients. The sensitivity of the analysis is automatically controlled to accommodate environmental noise on the fiber by increasing the envelope coefficients to make the analysis less sensitive at each cycle by adopting the larger value from the comparison and by decaying the envelope coefficients at each cycle over time to a smaller value down to a floor value.