You can find a variety of 3-axis accelerometers on our website that can meet different scenarios and needs. This time, we bring you the industrial grade, high stability, high precision, and low power ADI ADXL series three-axis accelerometers.
The Grove - 3-Axis Digital Accelerometer ±200g (ADXL372) is a ultra low power digital output MEMS Accelerometer, it can provide a 12-bit output at 100 mg/LSB scale factor. The most notable feature of this sensor is its ultra-low power consumption(only 22?A in measurement mode) and large measurement range(±200g). All the data output via the Grove I2C port, the I2C address is changeable. In order to meet a wider range of measurement needs, the sampling rate can be selected from 400Hz/800Hz/1600Hz/3200Hz/6400Hz, and the bandwidth can be selected from 200Hz/400Hz/800Hz/1600Hz/3200Hz. In addition to being used as an acceleration measurement, you can also use this module to do impact and shock detection.
The ADI ADXL Series Accelerometer includes four products that will meet your different range and output needs:
Product Measurement Range Output Port Power Consumption
Grove - 3-Axis Analog Accelerometer ±20g (ADXL356B) ±10
±20g Analog measurement mode:150 ?A
standby mode:21 ?A
Grove - 3-Axis Analog Accelerometer ±40g (ADXL356C) ±10g
±40g Analog measurement mode:150 ?A
standby mode:21 ?A
Grove - 3-Axis Digital Accelerometer ±40g (ADXL357) ±10g@51200 LSB/g
±20g@25600 LSB/g
±40g@12800 LSB/g Digital I2C measurement mode:200?A
Grove - 3-Axis Digital Accelerometer ±200g (ADXL372) ±200g Digital I2C measurement mode:22?A
Grove - 3-Axis Digital Accelerometer (LIS3DHTR) ±2g,±4g
±8g,±16g Digital I2C
SPI
GPIO ADC measurement mode:150 ?A
standby mode:21 ?A
Note
We've Released the Grove Selection Guide and hope to help you find the Grove suit you best.
Features
Large measuring range: ±200g
Ultralow power consumption: 22 ?A at 3200 Hz ODR
Selectable oversampling ratio and bandwidth
Deep embedded FIFO to minimize host processor load
Build-in 12-bit analog-to-digital converter (ADC)
Applications
Portable Internet of Things (IoT) edge nodes
Concussion and head trauma detection
Impact and shock detection
Asset health assessment
Pinout
