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The Bently Nevada 3500/44M-01-00 is a 4-channel dedicated vibration monitoring module for aeroderivative gas turbines within the 3500 machinery protection system, designed to continuously measure and monitor vibration, phase and keyphasor signals of gas turbine rotating components with configurable alarm thresholds, isolated analog outputs and integrated relay contacts for critical turbine equipment protection.
Description
| Parameter | Details |
|---|---|
| Model | 3500/44M-01-00 |
| Manufacturer | Bently Nevada (Baker Hughes) |
| Product Type | Aeroderivative Gas Turbine Vibration Monitoring Module |
| Product Series | 3500 Machinery Protection System |
| Number of Independent Vibration Input Channels | 4 |
| Supported Keyphasor Input Channels | Up to 2 |
| Supported Sensors | Velomitor velocity transducers, piezoelectric accelerometers, 3300 XL series proximity probes |
| Backplane Supply Voltage | +5 VDC, ±15 VDC from 3500 rack power supply |
| Typical Power Consumption | 7.7 W |
| Analog Output | 4-channel isolated 4~20 mA DC |
| Alarm Configuration | Dual programmable Alert/Danger alarm thresholds per channel |
| Relay Output | 4 Form-C relay contacts for alarm status indication |
| Communication Interface | Modbus RTU/TCP via rack backplane |
| ADC Resolution | 24-bit |
| Operating Frequency Range | 4 Hz to 30 kHz |
| Operating Temperature Range | -30°C to +65°C |
| Storage Temperature Range | -40°C to +85°C |
| Dimensions (W×H×D) | 24.4 mm × 241.3 mm × 241.8 mm |
| Net Weight | 0.91 kg |
| Protection Rating | IP20 |
| Mounting Method | Full-height slot installation on standard 3500 system rack |
| Compliance Certifications | CE, UL, ATEX, IECEx |
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About brand
The BENTLY 3500 system is a professional machinery protection and condition monitoring solution widely used in industries like oil and gas, power generation, and petrochemicals. It adopts a modular design, allowing flexible configuration of monitoring modules (e.g., vibration, temperature, and speed modules) to track key operating parameters of rotating equipment such as turbines and compressors. By collecting and analyzing data in real time, it can promptly identify issues like equipment imbalance or bearing wear, trigger alarms or shutdowns when thresholds are exceeded, and effectively prevent unexpected equipment failures to ensure production continuity.
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