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Analog Devices EVAL-RS485FD8EBZ Development board 1 pc(s)

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Technical specifications

Product type

Development board

Tool type

Development kit

Content

1 pc(s)

Interfaces

RS485

Documents & Downloads

Datasheet

Datasheet 2365032 Analog Devices EVAL-RS485FD8EBZ Development board 1 pc(s)

User & Safety Instructions

User & Safety Instructions 2365032 Analog Devices EVAL-RS485FD8EBZ Development board 1 pc(s)

Description

ICOMOX (Intelligent Condition Monitoring Box) - is a portfolio of open development platforms for the condition-based monitoring (CBM) of industrial plants, assets and structures. ICOMOX monitors operating conditions from the device interface, To identify potential faults and reduce the risks associated with operating and maintaining the equipment. This extends equipment life, reduces unplanned downtime, reduces maintenance costs, and opens up energy savings potential.

The iCOMOX is a dual purpose platform that OEMs can use to prototype CBM applications or as a ready-to-use solution for System Integrators (SIS) and Service Providers.

Autonomous mode operation with built-in AIfor the SRT-ICOMOX-POE-SEC-AI version
Autonomous mode anomaly detection algorithms allow users to configure a single preset state to be learned by the algorithm. As soon as a machine tutorial learns a preset state, deviations of the observed behavior relative to the preset state can be easily detected and automatically reported. The autonomous mode is particularly used for selecting sensors for AI systems and for training AI algorithms. Algorithms can be configured for a long training period (1 to 65535 minutes) and the learning result can be stored in a non-volatile memory.

The advantages of autonomous mode include:
· compared to the demo mode running on all other iCOMOX versions, the standalone mode has four times more internal (hidden) substates that extend learning in a single state
· Storage of the learned model in a non-volatile memory (in external flash)
· Ability to run the learning mode over a long period of time to learn the machine's behavior for several hours and to automatically change the inference mode
· Ability to control sensors involved in learning/inferential mode

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