IIS2DULPXTR Overview
The IIS2DULPXTR is a high-performance ultra-low-power 3-axis digital accelerometer designed for precise motion detection in compact industrial and consumer electronics. It features a wide dynamic range and an embedded machine learning core enabling advanced signal processing while minimizing system power consumption. Its small form factor and integrated functionalities make it ideal for applications requiring accurate motion sensing combined with efficient energy use. The device supports multiple operating modes and interfaces, ensuring seamless integration into complex systems. For more detailed information, visit IC 製造商.
IIS2DULPXTR Technical Specifications
| 參數 | 規格 |
|---|---|
| 軸心 | 三軸加速度計 |
| 測量範圍 | 可選擇 2 g / 4 g / 8 g / 16 g |
| 輸出資料速率 (ODR) | 1.6 Hz to 1600 Hz |
| 電源電壓 | 1.71 V 至 3.6 V |
| 電流消耗 | Down to 3 ??A in low-power mode |
| 介面 | I2C / SPI 數位介面 |
| 噪音密度 | 90 ??g/??Hz typical |
| 包裝 | 14-lead UDFN (2 x 2 x 0.7 mm) |
| 嵌入式功能 | Machine learning core for sensor data processing |
IIS2DULPXTR Key Features
- Advanced embedded machine learning core: Enables on-device signal processing to reduce host MCU load and power consumption.
- Wide selectable measurement ranges: Allows flexible adaptation to various vibration and motion sensing scenarios.
- 超低功耗： Supports prolonged battery life in portable and wearable applications through efficient power modes.
- High output data rates: Facilitates accurate and responsive motion tracking for fast-changing dynamics.
- Small 14-lead UDFN package: Optimizes PCB space usage, enabling integration in compact industrial and consumer devices.
- Robust digital interfaces (I2C and SPI): Simplifies communication with a wide range of microcontrollers and processors.
- Low noise performance: Ensures high accuracy in measurement, critical for sensitive industrial monitoring.
典型應用
- Industrial condition monitoring systems requiring precise vibration and tilt sensing to predict equipment maintenance needs and avoid downtime.
- Wearable devices that benefit from accurate motion tracking combined with extended battery life.
- Smartphones and tablets implementing gesture recognition and orientation detection.
- IoT sensors and asset tracking solutions where ultra-low power consumption and reliable motion detection are essential.
IIS2DULPXTR Advantages vs Typical Alternatives
This accelerometer offers significant advantages over typical alternatives by combining ultra-low power consumption with a machine learning core for enhanced on-chip data processing. Its flexible measurement ranges and high output data rates provide accurate detection across diverse applications, while the compact package supports miniaturized designs. The device??s low noise floor and robust digital interfaces improve signal fidelity and simplify integration, making it a superior choice for engineers seeking reliability and efficiency in motion sensing solutions.
暢銷產品
IIS2DULPXTR Brand Info
The IIS2DULPXTR is developed by STMicroelectronics, a global leader in semiconductor solutions. STMicroelectronics specializes in innovative MEMS sensors and accelerometers engineered for industrial, consumer, and automotive applications. This product reflects ST??s commitment to delivering high-precision, low-power devices that support intelligent sensing and embedded analytics. With comprehensive documentation and global technical support, STMicroelectronics ensures seamless integration and reliable performance for designers and sourcing specialists worldwide.
常見問題
What measurement ranges does this accelerometer support?
The device supports selectable measurement ranges of ??2 g, ??4 g, ??8 g, and ??16 g. This flexibility allows users to tailor sensitivity and range to specific application requirements, whether detecting subtle movements or more intense vibrations.
精選產品
How does the embedded machine learning core benefit system design?
The integrated machine learning core processes sensor data directly on-chip, reducing the workload on the host microcontroller. This leads to lower overall system power consumption and faster response times for motion detection and classification tasks.