Bently Nevada 3500/62-01-00 Process Variable Monitor

Advanced Process Monitoring Module for Industrial Machinery Systems

The Bently Nevada 3500/62-01-00 Process Variable Monitor provides accurate process measurement capabilities for industrial machinery protection applications. This module monitors critical parameters and integrates process data into the 3500 monitoring platform. Moreover, it helps operators evaluate equipment conditions through reliable signal processing and continuous data analysis.

The 3500/62-01-00 module supports multiple input channels for monitoring process variables from industrial sensors. Additionally, its modular design enables flexible installation within compatible 3500 rack systems. The unit improves operational awareness by connecting process information with machinery protection strategies.

Technical Specifications

Parameter	Details
Product Model	3500/62-01-00
Brand	Bently Nevada
Product Type	Process Variable Monitor
System Platform	3500 Machinery Protection System
Module Position	Rack-based monitoring module
Input Channels	6-channel process variable monitoring
Signal Type	Analog process input signals
Input Interface	Terminal block connection
Communication Interface	3500 rack communication interface
Dimensions	Approximately 241 mm × 24 mm × 241 mm
Weight	Approximately 0.90 kg
Power Supply	3500 rack power distribution system
Energy Storage	No internal energy storage components
Component Quantity	1 monitoring module assembly

Key Features and Benefits

The 3500/62-01-00 monitor delivers precise process data collection for demanding industrial environments. Furthermore, it supports flexible configuration options that allow engineers to match different application requirements.

The compact module design optimizes rack space usage while maintaining efficient signal processing performance. In addition, the unit simplifies system integration because it works with existing Bently Nevada 3500 monitoring infrastructures.

This process monitoring solution supports applications including turbines, compressors, pumps, and other rotating machinery systems. Therefore, maintenance teams can improve equipment analysis and develop more effective predictive maintenance programs.