EVAL-CN0540-ARDZ

Analog Devices
584-EVAL-CN0540-ARDZ
EVAL-CN0540-ARDZ

Mfr.:

Paglalarawan:
Multiple Function Sensor Development Tools IEPE CbM DAQ Board

Datasheet:
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Alamin pa ang tungkol sa Analog Devices EVAL-CN0540-ARDZ

May Stock: 5

Stock:
5 Maaaring Ipadala Agad
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Minimum: 1   Mga Multiple: 1
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Ext. Presyo:
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Presyo (PHP)

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Ext. Presyo
₱12,186.96 ₱12,186.96

Katangian ng Produkto Value ng Attribute Pumili ng Attribute
Analog Devices Inc.
Kategorya ng Produkto: Mga Tool sa Pag-develop ng Multiple Function Sensor
RoHS:  
Shields
Piezo Accelerometer Sensor
CN0540
Bulk
Brand: Analog Devices
Uri ng Produkto: Multiple Function Sensor Development Tools
Dami ng Pack ng Pabrika: 1
Subcategory: Development Tools
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Datasheet

Specification Sheets

CNHTS:
8543709990
CAHTS:
8473302000
USHTS:
8473301180
MXHTS:
8473300401
ECCN:
EAR99

IEPE Data Acquisition Board (EVAL-CN0540-ARDZ)

Analog Devices Inc. IEPE Data Acquisition Board (EVAL-CN0540-ARDZ) is a high-resolution, wide-bandwidth, high-dynamic-range Data Acquisition (DAQ) system that interfaces with the Integrated Electronics Piezoelectric (ICP®/IEPE) sensors. The EVAL-CN0540-ARDZ is designed to demonstrate vibration sensing for Condition-based Monitoring (CbM). By tracking the vibration analysis data over time, a fault or failure can be predicted, along with the source of the fault. Vibration sensing in an industrial environment adds additional challenges because of the need for robust and reliable sensing methods. Knowing the condition of a machine helps increase efficiency and productivity and creates a safer working environment.

CN0549 Condition Based Monitoring Dev Platform

Analog Devices Inc. CN0549 Condition Based Monitoring Development Platform (CbM) employs vibration sensing growing in importance for industrial applications. Companies seek to optimize machinery lifetime and performance and reduce the cost of ownership, while some are looking to develop new business models around the provision of such information. To provide an accurate representation of machinery that needs monitoring, large datasets must be collected to determine a baseline operating point for the equipment in normal operational modes and failure conditions. Once this data is collected, an algorithm or threshold detection routine can be created to provide the correct analysis for this equipment.

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