Bently Nevada 330980-51-CN Proximitor Sensor

Product Overview

The 330980-51-CN works as a Proximitor sensor within the Bently Nevada 3300 XL NSv series. This signal conditioner converts eddy current probe input into a proportional voltage output. Consequently, it delivers accurate vibration and position data for small rotating machinery. Power plants and compressor stations rely on this module for continuous protection.

Technical Specifications

Parameter	Value
Model	330980-51-CN
Series	3300 XL NSv
Function	Proximitor / Signal Conditioner
Compatible Probes	3300 XL NSv 5 mm and 8 mm
Output Sensitivity	7.87 mV/µm (200 mV/mil)
Linear Range	1.5 mm (5 mm probe)
Supply Voltage	-17.5 Vdc to -26 Vdc
Output Impedance	50 Ω nominal
Operating Temperature	-35°C to +85°C
Storage Temperature	-40°C to +100°C
Mounting	DIN rail or panel mount
Connector	3-pin coaxial
Weight	Approximately 255 g
Dimensions	100 mm × 75 mm × 25 mm
Frequency Response	0 to 10 kHz
Isolation	Galvanically isolated

Key Features and Interfaces

Furthermore, the 330980-51-CN provides a 3-pin coaxial interface for probe and extension cable connection. Its galvanic isolation blocks ground loops that distort measurement signals. In addition, the compact NSv design suits tight mounting spaces on smaller machines. Therefore, technicians install it quickly during short maintenance windows.

Installation and Compatibility

Moreover, this Proximitor pairs directly with 3300 XL NSv extension cables and proximity probes. The DIN rail mount simplifies cabinet layout inside crowded control rooms. Because the unit draws minimal supply current, it suits high-density monitoring racks. Subsequently, engineers integrate it into 3500 series systems and legacy 3300 installations alike.

Why Choose This Module

Additionally, the 330980-51-CN meets API 670 requirements for vibration monitoring chains. Its wide operating temperature supports placement near hot turbine casings. Meanwhile, the rugged housing resists vibration, moisture, and electromagnetic interference. As a result, maintenance teams gain dependable data for predictive maintenance strategies.