Bently Nevada 330180-X0-05 Proximitor Sensor

Product Overview

The 330180-X0-05 functions as a Proximitor sensor within the Bently Nevada 3300 XL system. This signal conditioner converts eddy current probe input into a proportional voltage output. Consequently, it enables accurate shaft vibration and position measurement in rotating equipment. Plants across power generation and oil refining trust this module for continuous machinery protection.

Technical Specifications

Parameter	Value
Model	330180-X0-05
Series	3300 XL
Function	Proximitor / Signal Conditioner
Input	3300 XL 5/8 mm or 8 mm probe
Output Sensitivity	7.87 mV/µm (200 mV/mil)
Linear Range	5 mm (5/8 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 ClickLoc 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 330180-X0-05 provides a 3-pin ClickLoc interface for probe and extension cable connection. Its galvanic isolation blocks ground loops that corrupt measurement signals. In addition, the module accepts both 5/8 mm and 8 mm probe inputs without hardware changes. Therefore, technicians can swap probes quickly during maintenance windows.

Installation and Compatibility

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

Why Choose This Module

Additionally, the 330180-X0-05 meets API 670 requirements for vibration monitoring chains. Its wide temperature range supports installations near hot turbine casings. Meanwhile, the robust housing resists vibration, moisture, and electromagnetic interference. As a result, maintenance teams gain reliable data for predictive maintenance programs.