Using the wearable sensor function of SensorTile.box, you can intuitively observe your movements and training conditions through curves when doing push-ups and planks.
This work monitors the child's sitting posture when writing. When the child sits upright, no prompt is generated. When the child lowers his head, the sensor light flashes to signal an alarm!
Common robotic arm controls are developed from CNC, emphasizing constant speed and stability in the motion process. Many controllers use hybrid PID for speed control, which generates great acceleration during the startup phase in order to quickly reach the set speed. Due to the solid state of the solid itself Stiffness, this drastic speed change is very effective for CNC machining scenarios or general solid handling scenarios. However, it will have a huge impact in liquid handling scenarios, so new control methods need to be proposed. This control method must control the acceleration
This project uses the LSM6DSOX+STEVAL-MKI109V3 mode for preliminary sensor learning and research, mainly from training the acceleration sensor to detect vibration and recording vibration waveforms, training the gyroscope sensor to detect the vibration direction and offset, and recording the waveform for analysis; combined with the acceleration sensor and the action data of the gyroscope sensor can determine the vibration intensity and direction of the wind turbine tower under various working conditions; in practical applications, the LSM6DSOX sensor is combined with the low-power chip STM32L010RBT6 chip, and the main control board on the local side leads to an alarm relay. The outlet is used for alarm output on the wind turbine tower side. It is connected to the wind turbine scada system through 485 serial port communication to upload the recorded data on the local side to provide real-time feedback on the working status of the wind turbine tower. It can be used to analyze the vibration reverse and wind turbine tower vibration. Swing direction recording can also record and analyze the natural frequency of the wind turbine tower under normal conditions and the natural frequency during faults. The multi-faceted data forms a wind turbine tower disaster warning system that can be sensed in advance;
This project uses LSM6DSOX high-performance sensor and LIS25BA high-precision bone conduction sensor to control the four-axis robotic arm. By combining FMS and MLC with LSM6DSOX, the robotic arm can grab and put down items. Through LIS25BA, the vibration can be recognized and the steering gear can be controlled to complete the corresponding actions.
My initial idea for the "Badminton Training Device" project was to sense the form and intensity of the racket swing, whether it hit the badminton and where it was hit, etc., record the quality of all swings after a game, and combine it with the host computer to make a badminton shot. Play the practice analysis system. The MLC and FSM modules in LSM6DSOX can analyze and identify actions, which greatly reduces the data processing requirements of the MCU and can save resources to complete prompt or record functions.
LSM330D adapter board for standard DIL24 socket
LSM330DLC adapter board for standard DIL24 socket
AIS328DQ adapter board for standard DIL24 socket
Professional MEMS Tools: ST MEMS Adapter Board based on STM32F401VE and compatible with all ST MEMS adapters
eMotion: ST MEMS adapter board based on STM32F103 and compatible with all ST MEMS adapter boards
L3GD20 adapter board for standard DIL24 sockets
LSM303DLHC adapter board designed to plug into standard DIL24 sockets
LIS3DH adapter board for standard DIL 24 sockets
LIS331HH adapter board for standard DIL24 socket
LIS331DLH adapter board for standard DIL 24 sockets
LIS344ALH adapter board for standard DIL24 socket
LPS22HB adapter board for standard DIL24 socket
Multi-sensor predictive maintenance kit with IO-Link stack v.1.1