Product overview
The BWSENSING BW-VG400C is an inclination-sensing component for integration into unmanned aircraft, electro-optical pods, stabilization platforms and other vehicle or monitoring systems. Its packaged body measures 60 × 59 × 29 mm, with a specified weight of 280g including the cable and 360g including packaging. It measures pitch through ±90° and roll through ±180°. Dynamic accuracy is 0.2°, while static accuracy and resolution are both 0.01°, making the distinction between moving and stationary measurement relevant to integration requirements.
Integration options include selectable RS232, RS485 or TTL output, serial communication from 2400 to 115200 baud and a high-performance binary protocol. Startup delay is below 50ms, and maximum output frequency is 500Hz. Processing incorporates Kalman filtering, nonlinearity and orthogonality compensation, and bias tracking for drift elimination. The temperature range is -40°C to +85°C; shock resistance is 2000g for 0.5ms, three times per axis. The hardware is a packaged sensor component, with interface selection forming part of its configuration.
Specifications
| Specification | Value & conditions |
|---|---|
| Product type | BW-VG400C high-precision digital dynamic inclination sensor |
| Dynamic accuracy | 0.2° |
| Static accuracy | 0.01° |
| Resolution | 0.01° |
| Inclination range | Pitch ±90°; roll ±180° |
| Packaged sensor dimensions | L60 × W59 × H29 mm |
| Weight with cable | 280gIncluding cable. |
| Weight with packaging | 360gIncluding packaging. |
| Startup delay | Less than 50ms |
| Maximum output frequency | 500Hz |
| Serial communication rate | 2400 to 115200 baud |
| Digital output format | High-performance binary protocol |
| Interface options | RS232, RS485 or TTLSelectable interface output. |
| Temperature range | -40°C to +85°C |
| Mean time between failures | ≥30000 hours |
| Shock resistance | 2000g0.5ms; 3 shocks per axis. |
| Compensation | Nonlinearity compensation and orthogonality compensation |
| Drift correction | Special bias-tracking algorithm for drift elimination |
| Filtering | High-performance Kalman filtering algorithm |
| Application areas | Unmanned underwater vessels; wind turbine tower sway monitoring; platform stabilization; large ships; electro-optical pods; autonomous driving; special-purpose vehicles; unmanned aircraft |
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