The BENTLY 3500/40M 140734-01 large card is a significant component in the Bently Nevada 3500 Machinery Monitoring System, designed for industrial applications where precise monitoring and protection of machinery is critical.

**Product Name:**

BENTLY 3500/40M 140734-01 Large Card

**Product Description:**

The BENTLY 3500/40M 140734-01 large card is part of the Bently Nevada 3500 Series Monitoring System, a widely used system in the industrial sector for monitoring the condition of machinery such as turbines, compressors, pumps, and motors. This large card plays a crucial role in processing and analyzing data related to vibration, temperature, and other critical parameters to ensure the machinery operates within safe limits and to alert operators to potential issues before they escalate.

**Product Parameters and Specifications:**

– **Part Number:** 140734-01
– **Series:** BENTLY Nevada 3500
– **Type:** Large Card
– **Application:** Machinery Monitoring and Protection
– **Input Channels:** Multiple channels for various sensor inputs (vibration, temperature, etc.)
– **Output:** Provides real-time data to the monitoring system
– **Compatibility:** Designed to work with other components of the Bently Nevada 3500 System
– **Power Requirements:** Typically operates on standard industrial power supply
– **Mounting:** Designed for rack mounting within the monitoring system chassis
– **Communication Interface:** Interfaces with the main monitoring system via proprietary communication protocols

**Product Use:**

The BENTLY 3500/40M 140734-01 large card is used primarily for:

– Monitoring vibration levels of critical machinery components.
– Detecting anomalies and deviations from normal operating conditions.
– Providing early warnings and alarms to prevent catastrophic failures.
– Integrating data with overall plant monitoring and control systems.
– Ensuring the overall safety, reliability, and efficiency of industrial machinery.

This large card is a key element in maintaining operational integrity and preventing costly downtime by enabling proactive maintenance based on real-time data analysis of machinery health.