Graded early warning system for rollover of heavy-duty truck based on time-varying interactive kalman filtering and early warning method thereof

A graded early warning system for rollover of heavy-duty truck based on time-varying interactive Kalman filtering, comprising:

• an infrared speed measuring module;
• a gyroscope;
• a humidity signal acquisition sensor;
• a bluetooth data transmission module;
• and
• a main control chip;
• wherein the infrared speed measuring module, the gyroscope, the humidity signal acquisition sensor are respectively connected with input ends of the main control chip through control lines;
• a video output end of the main control chip is connected with a liquid crystal display through video signal line;
• the main control chip is wirelessly connected with a mobile phone through the bluetooth data transmission module,
• wherein the infrared speed measuring module, the gyroscope and the humidity signal acquisition sensor are configured for collecting index data of vehicle acceleration, degree offset, road humidity respectively,
• wherein the main control chip is configured for:
• using a rigid body model of an automobile as physical model for analyzing the rollover threshold of truck under real-time road condition;
• obtaining the index data of vehicle acceleration, degree offset, road humidity;
• constructing a graded time-varying interactive Kalman filtering model;
• completing date processing by using the time-varying interactive Kalman filtering and integration of data mining technology of quaternion algorithm by:
• processing the index data of vehicle acceleration, degree offset, road humidity according to the Kalman filtering model for compensating sensor drift and measurement noise, obtaining an initial attitude under static conditions by using a three-axis accelerometer and a three-axis magnetometer, processing the initial attitude by the quaternion algorithm, and obtaining a current attitude of the truck based on the processed index data of vehicle acceleration, degree offset, road humidity, together with the processed initial attitude;
• carrying out mechanical analysis of the rigid body model to obtain condition equation of rollover;
• and
• predicting a rollover of the truck based on the current attitude of the truck and the condition equation of rollover.