Distributed Strain Sensing
Distributed Strain Sensing (DSS) is an advanced technology that employs optical fibers to remotely measure and monitor strain variations over extensive distances.
The technology utilizes the Brillouin backscatter phenomenon, it detects and precisely maps strain changes along the fiber with high accuracy.
Technology
DSS transforms fiber optic cables into precise strain monitors spanning extensive distances. Utilizing Brillouin scattering, continuous laser pulses are sent through the fiber, and variations in the frequency shift of the backscattered light are meticulously analyzed to detect strain changes along the fiber.
This allows DSS systems to provide real-time strain profiling, offering invaluable insights into structural deformations and integrity.
DSS Features
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Continuous Strain Monitoring
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Micro-strain Detection
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Extensive Coverage
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Immediate Anomaly Alerts
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Environmental Resilience
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Low Maintenance
Landslide
Fiber optic cables are installed along vulnerable slopes and hillsides to monitor strain variations in the ground. By detecting subtle deformations and shifts in soil or rock structures in real time, DSS can identify early signs of ground movement, enabling timely warnings to avert landslides before they occur.
Bridge and Infrastructure Monitoring
Bridges and infrastructure are monitored using DSS, where fiber optic cables are embedded within structural elements to measure strain variations. Continuous real-time detection of stress and deformation along the fibers allows for early identification of potential structural issues
Pipeline
DSS is utilized in pipeline monitoring by embedding fiber optic cables alongside the pipeline to continuously measure strain and deformation. This identifies stress points, ground movement, and structural weaknesses, enabling early intervention to prevent leaks, ruptures.
Applications
Safety & Incident Detection
Track Buckling, Excessive Load, Potential Accidents
Strain variations along railway tracks are continuously monitored using DSS to enhance safety and incident detection. By detecting anomalies such as track buckling, excessive loads, or structural deformations in real time, potential accidents are prevented through early warnings and timely interventions.