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Strain Sensors for Industrial Internet of Things (IIOT)

  • Truly Wireless
  • Contains an strain sensor, temperature sensor, pressure sensor & humidity sensor
  • Can be adhesive mounted, stud mounted or magnet mounted on static structures such as dams, bridges etc.
  • Installation time is as less as 5 minutes
  • Meets stringent industry standards such as: ASME Class 1 Div, IP65, FCC & IC (Currently under testing, however, the preliminary product design is likely to pass qualifications as per leading standardization organization)
  • Strain Resolution – 1 µStrain
  • Rated for -45C to 125C.
  • Ultra low power design enables a battery life of a minimum of 5 years
  • Predicts the remaining time before fatigue failure of industrial assets
  • Continuously monitors the stresses that the asset is exposed to and signals any suspicious movement
  • Avoid catastrophic failures that can cause millions in lost revenues and billions in reputational losses
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Fault Diagnosis

  • Real time Structural diagnostics such as indicating whether it breached the critical stress or strain limit
  • Failure potential of the joints
  • Critical bending limit of the slabs
  • Bearings inner race and out race fault
  • Patent pending combination of specialized signal processing method and specialized neural networks method ensures a least error rate, fastest convergence rate and catches faults with prove 99% accuracy or more.
  • Specialized neural networks algorithm used for autocalibration of sensors giving highly consistent and noise free readings
  • Multi sensor fusion using Deep Learning with specialized neural networks that provides absolutely low error rate of the order of 1e-20.
  • Combines physics based model with the data based model to provide better detection
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Neural Networks & Kernel method based Remaining Useful Life estimation

  • First such algorithm in the industry which uses artificial intelligence, material properties & IoT
  • Combination of specialized neural networks & kernel based extrapolation methods used for predicting remaining fatigue life with more than 90% accuracy.
  • Gathers and learns from the material data and applies it to the real time strain sensor data
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Secure data transmission to Cloud server

  • Complies with TLS 1.2 Security Protocol
  • Data traffic originates from sensor, no connection from server
  • Completely server less architecture provided
  • Sensor data stored locally with scheduled uploads to cloud server using most cyber secure platform (Certified by UL) available in the world
  • Complete data pipeline is encrypted
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Real-time alerts and reports

  • Week incipient fault alerts
  • Text & Email alert system available
  • Low battery alert available
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User-friendly dashboard available on mobile devices

  • Approved users stay updated on the health of their equipment from anywhere at any time.
  • Data can be accessed for independent analysis.
  • Data, images, drawings can be tied to individual sensors to provide technicians with information on the location of the equipment and sensors as well as other user-defined information such as P&ID’s etc.
  • Fatigue & Stress Cycles data and overall structural health of the asset available
  • Patented Platform for the automatic detection of the high stress points enables quick sensor installation turnaround and very high quality predictions

FatigueLF

Install FatigueLF

Wireless sensors mounted at the optimal location (estimated by Nanoprecise’s patented platform automatically) on the asset

Collect

On the cloud, data is processed in real time using sophisticated signal processing methods

Analyze

Patented and state of the art deep learning algorithms learn from the processed data and estimate the following:
- Remaining time to fatigue failure

Control

The real time health condition of the asset is available on the dashboard available on tablet, smartphone and desktop.