Intrusion Detection Algorithm With Reduced Tuning
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Solution Overview
Problem
Conventional Distributed Acoustic Sensing (DAS) systems require extensive tuning and calibration for each installation, which is time-consuming and sensitive to environmental conditions like weather, leading to potential vulnerabilities in perimeter security systems.
Innovation Solution
A method for analyzing monitoring signals from optical fibers that reduces the need for tuning by dividing the fiber into blocks, collating data streams into common streams, and applying an algorithm that compares coefficient values with threshold values to detect disturbance events, without relying on recorded signatures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional DAS systems use extensive tuning and calibration for each installation, then measurement precision and reliability are improved, but installation time and system complexity increase significantly
Solution Approach 1:
The patent divides the optical fiber into multiple discrete zones along its length, with each zone having independent detection parameters and thresholds. This segmentation allows the system to process and analyze disturbances in each zone independently, eliminating the need for system-wide tuning and calibration while maintaining detection accuracy. The fiber is divided into zones that can be monitored separately, reducing installation complexity.
Solution Approach 2:
The patent implements automatic adjustment of detection parameters including sensitivity thresholds, zone boundaries, and detection criteria based on environmental conditions and historical data. The system dynamically modifies these parameters without requiring manual tuning, adapting to changing conditions such as temperature variations, wind, and rainfall while maintaining optimal detection performance.
2Measurement precision
If DAS systems are highly sensitive to environmental conditions, then detection capability is improved, but false alarms increase due to weather effects
Solution Approach 1:
The patent converts environmental disturbances that cause false alarms into beneficial calibration data. By analyzing patterns in weather-related disturbances (wind, rain, temperature changes), the system learns to distinguish these from actual intrusions and adjusts its detection algorithms accordingly. Environmental noise is transformed into training data that improves the system's ability to reject false alarms while maintaining sensitivity to real threats.
Solution Approach 2:
The patent implements feedback mechanisms where detection results and environmental conditions are continuously monitored and used to adjust detection parameters. When weather conditions are detected, the system automatically modifies sensitivity thresholds and detection criteria for affected zones, reducing false alarms while maintaining intrusion detection capability. Historical detection data feeds back into the system to refine future detection decisions.
3Reliability
If manual tuning and calibration are performed for each installation, then system reliability is improved, but productivity and ease of installation deteriorate
Solution Approach 1:
The patent enables the DAS system to perform self-configuration and self-calibration automatically during installation. The system automatically divides the fiber into zones, sets initial detection parameters, and adapts to environmental conditions without requiring manual tuning by technicians. This self-service capability maintains system reliability while dramatically increasing installation speed and reducing the skill level required for installation.
Solution Approach 2:
The patent pre-configures detection parameters, zone boundaries, and sensitivity thresholds before deployment based on typical installation scenarios. The system comes pre-programmed with detection algorithms and parameter sets that can be automatically applied, eliminating the need for on-site tuning and calibration while ensuring consistent reliable performance across different installations.
4Measurement precision
If frequent recalibration is required to maintain performance, then measurement precision is improved, but loss of time and operational complexity increase
Solution Approach 1:
The patent implements dynamic parameter adjustment where detection sensitivity, thresholds, and zone configurations automatically adapt to changing environmental conditions and operational contexts. The system continuously monitors performance and adjusts parameters in real-time without requiring manual recalibration, maintaining high detection accuracy while eliminating time-consuming recalibration procedures. Detection parameters are made dynamic rather than static, allowing the system to respond to changing conditions autonomously.
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
This approach enables more efficient and less labor-intensive installation of DAS systems, while maintaining sensitivity to intrusion events even in adverse weather conditions, thereby enhancing perimeter security without the need for frequent recalibration.
Implementation Method 1
A small proportion of the light travelling in a fiber is reflected back by the process known as Rayleigh Backscatter. Vibrations from the surrounding environment, will disturb the light in the fiber and will therefore be observed by the DAS interrogator.
Data Source
AI summary
An optical fiber is monitored for an intrusion event where reflected optical signals are divided into streams each associated with a respective location on the optical fiber. Blocks of the streams are selected each containing a plurality of streams and the streams are collated, for example by averaging, to create a single stream to which an algorithm is applied to create coefficients which are compared with a threshold value to generate an output indicative of disturbance of the fiber by an intrusion event. Each block representative of a length of the fiber is thus treated as a zone and the detection algorithm is applied to each. This creates a DAS system that does not require unique tuning as each zone is independently monitored. Applying the above zone principles and algorithms to the DAS system also provides a high level of nuisance alarm and false alarm rejection.