The Bently Nevada 3500/25-01-01-01 Enhanced Keyphasor Module is an advanced vibration monitoring solution specifically designed for industrial machinery health management. It offers precise data for predictive maintenance, enabling operators to anticipate potential failures and minimize downtime.
Model Number:3500/25-01-01-01
Input Voltage Range:9 to 32 VDC
Output Signal Type:4-20 mA or 1-5 V DC
Sampling Rate:Up to 2 kHz
Signal Processing:Digital signal processing for enhanced accuracy
Temperature Range:-40°C to +85°C
Enclosure Rating:IP65
The Bently Nevada 3500 Enhanced Keyphasor Module offers unparalleled accuracy in monitoring motor performance, ensuring minimal downtime and maximum productivity. Its advanced signal processing capabilities enable early detection of potential issues, allowing for proactive maintenance.
Engineered for durability and robustness, this module can withstand harsh industrial environments, making it suitable for applications in power plants, manufacturing facilities, and other sectors requiring high levels of reliability.
The compact design and modular architecture facilitate easy installation and integration, minimizing the need for extensive wiring and reducing installation time. This streamlined approach enhances efficiency and simplifies system management.
With its user-friendly interface and comprehensive diagnostic functions, operators can quickly access critical data and trends, optimizing maintenance schedules and improving overall system performance.
Backed by a comprehensive warranty and supported by Bently Nevada’s global service network, users can enjoy peace of mind knowing they have access to expert assistance and the latest technology updates. Choose the Bently Nevada 3500 Enhanced Keyphasor Module for enhanced motor protection and analysis, leading to increased safety and operational excellence.
The Bently Nevada 3500/25-01-01-01 Enhanced Keyphasor Module is an advanced vibration monitoring solution specifically designed for industrial machinery health management. It offers precise data for predictive maintenance, enabling operators to anticipate potential failures and minimize downtime.